faculty of electrical engineering - aktualności · artificial intelligence, patrick henry winston,...

1

FACULTY OF ELECTRICAL ENGINEERING LIST OF COURSES FOR ACADEMIC YEAR 2017/2018

If you have any questions regarding courses please contact person responsible for the course or faculty

coordinator directly.

Course title Person responsible for

the course

Semester

(winter/summer)

ECTS

points

Antennas and EM wave propagation Stanisław Gratkowski winter 3

Artificial Intelligence In Automation and Robotics Krzysztof Jaroszewski winter or summer 3

B.Sc. Thesis winter or summer 15

Basic Course of Metrology Artur Wollek winter 4

Basics of Power Electronics Marcin Hołub winter or summer 3

Biomedical Signal Processing and Analysis Joanna Górecka winter or summer 4

Biomedical Technology Equipment Joanna Górecka winter or summer 3

Computer Animation Przemysław Mazurek winter or summer 4

Computer Graphics and Visualisation Krzysztof Okarma winter or summer 5

Computer Methods for Mathematical Computations Marcin Ziółkowski winter or summer 4

Computer Networks Piotr Lech winter 4

Computer Vision and Image Processing Krzysztof Okarma winter or summer 6

Control of Electric Drives Marcin Hołub winter or summer 4

Control of Mobile Robots Adam Łukomski winter or summer 2

Digital Technique Joanna Górecka winter or summer 4

Electric Power Network Michał Zeńczak winter or summer 3

Electrical Circuit Analysis with Matlab Marcin Ziółkowski winter or summer 3

Electrical Power Engineering Michał Zeńczak winter or summer 6

Electromagnetic Field and the Human Body Stanisław Gratkowski winter or summer 3

Electromagnetic Methods of Non-destructive Testing Tomasz Chady winter or summer 4

Electronic Devices and Circuits Witold Mickiewicz winter or summer 4

Elements of Laser Optics Andrzej Ziółkowski summer 3

Elements of Psychoacoustics and Electroacoustics Witold Mickiewicz winter or summer 4

EM Fields Effects in Living Organisms Michał Zeńczak winter 2

Fiber Optic Access Networks (Foam) Patryk Urban Summer 3

Fiber Optics Instalation Grzegorz Żegliński Winter 3

Fundamentals of Engineering Electromagnetics Stanisław Gratkowski winter or summer 3

Fundamentals of Web Development Przemysław Włodarski winter or summer 5

High Voltage Engineering Szymon Banaszak winter or summer 4

Industrial Electronics PhD Research Lab Marcin Hołub winter or summer 10

Introduction to Control Engineering Paweł Dworak winter or summer 4

2

Introduction to Cryptography Maciej Burak winter or summer 3

Introduction to Electric Circuits – part 1 Tomasz Chady winter or summer 4

Introduction to Electric Circuits – part 2 Tomasz Chady winter or summer 4

Introduction to Multisensor Data Fusion Grzegorz Psuj winter or summer 2

Introduction to Sound Recording Technology Witold Mickiewicz winter or summer 4

M.Sc. Thesis winter or summer 20

Machine Learning Adam Krzyżak summer 6

Managing Model-Based Development Krzysztof Pietrusewicz winter or summer 3

Medical Imaging Systems Piotr Okoniewski winter or summer 3

Modeling of Complex Systems with the use of SysML Krzysztof Pietrusewicz winter or summer 3

Modern Electrical Machines Ryszard Pałka winter or summer 6

Multistructured Optical Fibres Applications Ewa Weinert-Rączka winter 2

Network Systems Administration Piotr Lech summer 4

Network Traffic Przemysław Włodarski winter or summer 5

Non-Destructive Testing (NDT) using radiographic (X-ray)

and terahertz method Tomasz Chady winter or summer 4

Nonlinear Control Adam Łukomski winter or summer 3

Object-Oriented Programming in C# Marcin Ziółkowski winter or summer 4

Optimization Theory Marcin Ziółkowski winter or summer 4

Pattern Recognition and Classification Adam Krzyżak summer 4

Power Electronics for Renewable Energy Sources Marcin Hołub winter or summer 3

Power System Engineering Michał Balcerak winter or summer 3

Power system protection Michał Zeńczak winter or summer 2

Problem-Solving Workshop Joanna Górecka winter or summer 5

Programmable Automation System Based on PLC and HMI Krzysztof Jaroszewski winter or summer 3

Programmable Logic Devices Witold Mickiewicz winter or summer 4

Renewable Energy Sources Michał Balcerak winter or summer 2

Requirements Management in Research Projects on Complex

Systems Krzysztof Pietrusewicz winter or summer 3

Robot Dynamics and Control Rafał Osypiuk summer 2

Selected Topics in Nonlinear Photonics Ewa Weinert-Rączka summer 2

Simulation and Design of Power Electronic Converters Marcin Hołub winter or summer 3

Sound System Design Witold Mickiewicz winter or summer 4

Statistical Methods in ICT Przemysław Włodarski winter or summer 5

Telemedicine Sławomir Kocoń winter or summer 3

Terahertz Technique Przemysław Łopato winter or summer 2

Ultrasonic and Radiographic Nondestructive Testing Marcin Ziółkowski winter or summer 2

Visual Programming in LabVIEW Paweł Dworak winter or summer 3

Walking Robots Adam Łukomski winter or summer 3

3

Course title ANTENNAS AND EM WAVE PROPAGATION

Field of study Electrotechnics, electronics

Teaching method Lectures with simple experiments;

laboratory –measurements and computer simulations of antenna structures

Person responsible for

the course

Stanisław Gratkowski

(laboratory – Przemyslaw

Lopato)

E-mail address to the

person responsible for

the course

[email protected]

([email protected])

Course code

(if applicable) ECTS points 3

Type of course Obligatory Level of course bachelor/master

Semester Winter Language of instruction English

Hours per week

3 hours

(lectures – 2, laboratory –

1, other organization is

possible)

Hours per semester

45 hours

(lectures – 30,

laboratory – 15)

Objectives of the

course

This course is intended to present foundations of antenna and microwave engineering.

Numerical modeling and measuring techniques are also described.

Entry requirements/

prerequisites Basic course of mathematics and physics (electromagnetics)

Course contents

Electromagnetic waves, Maxwell’s equations, antenna parameters, types of antennas, arrays,

smart antennas, transmission lines, waveguides, reflection coefficient, SWR, impedance

matching, Smith chart, S-parameters, active and passive microwave devices, computer aided

analysis of antennas and microwave instruments (numerical techniques review),

measurements of antennas and microwave devices.

Assessment methods Lectures – written and oral exam; laboratory – continuous assessment

Learning outcomes

During the course, students will gain a basic knowledge of the operation, design and

modeling of antenna and microwave systems utilized in electrotechnics, electronics and

telecommunication.

Required readings

1. Balanis Constantine A., Antenna Theory: Analysis and Design, John Wiley & Sons, 2005

2. Bansal Rajeev, Fundamentals of engineering electromagnetics, CRC Press

Taylor & Francis, 2006

3. Collin Robert E., Foundations for microwave engineering, John Wiley & Sons, 2001

Supplementary

readings

1. Milligan Thomas A., Modern antenna design, John Wiley & Sons, 2005

2. Hong J.S., Lancaster M.J., Microstrip filters for RF/Microwave applications, John Wiley &

Sons, 2001

Additional information -

4

Course title ARTIFICIAL INTELLIGENCE IN AUTOMATION AND ROBOTICS

Field of study

Automatic Control and Robotics, Electrical Engineering, Mechanical Engineering,

Management and Production Engineering , Information and Communications Technology,

Electronics and Telecommunications, Architecture and Urban Planning - Civil Engineering

Teaching method Lecture, project, laboratory


the course Krzysztof Jaroszewski

E-mail address to the person

responsible for the course [email protected]

Course code

(if applicable) Compulsory/optional ECTS points 3

Type of course Level of course bachelor

Semester Winter or summer Language of instruction English

Hours per week 1 (L) 1 (P) 1 (Lab) Hours per semester 1 (L) 1 (P) 1 (Lab)

Objectives of the

course

To deliver the basic knowledge about artificial intelligence with special focus on genetic

algorithms, neural networks and fuzzy logic. Student achieve competence of using

mentioned methods in task of optimization, modeling, control, recognition and

classification – Matlab environment.

Entry requirements/

prerequisites Elementary knowledge in the subject of Mathematics and Physics

Course contents

Perceptron – decisive boundary. Multilayer neural network – backpropagation learning

algorithm. Recursive neural networks. Selection, crossing and mutation – steps of classical

genetic algorithms and genetic operators. Membership functions, rules editing,

fuzzyfication and defuzzyfication, concluding in expert and fuzzy systems.

Assessment methods Grade

Project work

Learning outcomes Ability to define basic subjects connected with artificial intelligence. Skills in implementing

and using proper method of artificial intelligence.

Required readings

Curse materials

Manuals of Matlab/Simulink environment

Artificial Intelligence: A Modern Approach, Stuart Russell, Peter Norvig, ISBN 0136042597

Supplementary

readings

1. Artificial Intelligence, Patrick Henry Winston, ISBN: 0201533774

2. Artificial Intelligence: A New Synthesis, Nils J. Nilsson, ISBN: 1558604677

Additional information Max 12 persons.

5

Course title B.Sc. Thesis

Teaching method Individual work with the thesis supervisor


the course

Depends on the subject of the

thesis


responsible for the course

Course code


Type of course Obligatory Level of course bachelor


Hours per week Hours per semester 12 hours

Objectives of the

course

This course is intended to help students with their B.Sc. thesis. The work is either a project

or a research. It can result in e.g. creating a computer program, laboratory work station, a

device-model or presenting results of research carried out using professional devices or

programs.

Entry requirements/

prerequisites

- Knowledge of basic issues related to the subject of the thesis

- Ability to formulate technical texts and prepare drawings and diagrams presenting

gained results

Course contents

Doing a B.Sc. thesis is in fact realization of a typical engineering task that starts with

formulating a problem and making assumptions, analyzing current state of the art and

defining the method of realizing the aim of the work. At the end of the task, the student

formulates conclusions and prepares written description of performing the task, its results

and analysis.

Assessment methods Continuous assessment and instructions given by the supervisor

Learning outcomes

Knowledge of modern solutions related to the subject of the thesis, ability to write technical

reports and prepare related multimedia presentations, ability to find the necessary

information in the literature and technical documentation

Recommended

readings Depends on the subject of the thesis

Additional information Please contact the faculty Erasmus coordinator to discuss the details of the course.

6

Course title BASIC COURSE OF METROLOGY

Field of study Electrical Engineering

Teaching method Lecture / laboratory


the course Artur Wollek



Course code


Type of course compulsory Level of course bachelor

Semester winter Language of instruction English

Hours per week 1 L / 2 Lab Hours per semester 15 L / 30 Lab

Objectives of the

course

To provide a basic knowledge in the field of metrology. The student learns: typical methods

of measurement methods and tools necessary for analyzing the results of the

measurements, as well as the current state and development trends in the field of sensors,

transducers and measurement systems.

Entry requirements/

prerequisites Mathematics, Physics

Course contents

Basic concepts of metrology, units and the measurement system, measurement standards.

Measuring scales. Basic methods of measurement. Analysis of accuracy of measurement:

systematic and random errors, the uncertainty of measurement. Electrical quantities

measurement. Measurement of voltage and current. Measurement of resistance and

impedance. Non-electrical quantities measurement. Measurement of the frequency, period

and time. Classification of sensors and transducers for measuring non-electrical values.

Static and dynamic properties of sensors and transducers. Temperature measurement

methods. Measurement of rotational speed. Pressure measurements. Measurement of the

magnetic properties of solids. Measuring systems. ADC and DAC converters – structure, the

principle of operation, properties. DAQ cards in measuring systems. Interfaces in measuring

systems. Software of the measurement systems.

Assessment methods Lectures – written exam / Laboratory – continuous assessment

Learning outcomes

The student can choose the typical measurement methods and appropriate sensors and

transducers, as well as to assess the usefulness of new solutions for the implementation of

the tasks associated with electrical engineering.

Required readings

1. Evaluation of measurement data – Guide to the expression of uncertainty in

measurement, JCGM, 2008

2. Northrop R.B.: Introduction to instrumentation and measurements, CRC Press, 2005

3. Sidor T.: Electrical and Electronic Measurement and Instrumentation, AGH, 2006

4. Sydenham P.H.: Handbook of Measurement Science, John Wiley & Sons Ltd., 1983

5. The Metrology Handbook, ASQ Quality Press, 2004

6. Tumański S.: Principles of electrical measurement, Taylor&Francis Group, 2016

Supplementary

readings

1. Bewoor A.K., Kulkarni V.A.: Metrology&Measurements, Tata McGraw-Hill, 2009

2. Kularatna N.: Digital and analogue instrumentation testing and measurement, IEE, 2004

Additional information

7

Course title BASICS OF POWER ELECTRONICS

Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics

Teaching method lecture /laboratory


the course Marcin Hołub



Course code



Semester winter or summer Language of instruction English

Hours per week 1L/2Lab Hours per semester 15 L

30 Lab

Objectives of the

course

Student will be able to:

- distinguish basic types of power semiconductors.

- calculate basic losses and cooling requirements.

- distinguish basic rectifier topologies and their main properties,

- draw basic waveforms for different types of loads.

- distinguish basic types of AC/AC converters.

- give basic properties and characteristics for main types of switched mode power

supplies.

- perform basic calculations for main circuit components and adjust component

type and kind.

- use CAD software for basic simulations and basic types of projects.

- perform basic project for a small scale power converter.

- analyze basic structures of power converters.

Entry requirements/

prerequisites Electronics, basics of electrical engineering

Course contents

Power electronics: past and present, perspectives, connections with other technical

branches Semiconductor power devices: thyristors (SCR, GTO, IGCT), power transistors (BJT,

MOSFET, IGBT). Power modules. ontrol of semiconductor power devices, power transistor

driving stages Static and dynamic losses of power semiconductors. Thermal characteristics,

cooling methods. Over-voltage, over-current and short-circuit protection systems Rectifiers

– one phase, three phase. Characteristics under resistive, RL and RLE load. Controlled

rectifiers – thyristor rectifiers with the 4T and 6T topology. Characteristics under resistive, RL

and RLE load. Hard switching DC/DC choppers, single and three-phase. Boost and

buck/boost converters, smps systems topologies, basics of magnetics and design of chokes

and HF transformers. Transistor inverters – single and three-phase topology. Methods of

voltage and current shaping (PWM,SVM, harmonics elimination). Special converters (PFC, E-

class). Electric drive converter systems, power electronics for photovoltaic and wind energy

conversion.

Assessment methods

Written tests

Project work assessment

Laboratory reports

8

Learning outcomes

Ability to distinguish properties of power semiconductors. Ability to define and measure

basic waveforms and characteristics of AC/DC, AC/AC, DC/DC and DC/AC converters. Ability

to analyze and choose converter topology. Basic knowledge on converter construction.

Basic knowledge on converter simulation

Required readings

1. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-1McGrawHill

2009

2. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill 1999

3. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7

Supplementary

readings


Course title BIOMEDICAL SIGNAL PROCESSING AND ANALYSIS

Field of study

Teaching method lectures, labs (also in hospital), project


the course Joanna Górecka



Course code


Type of course compulsory Level of course bachelor or master


Hours per week 3 (1L, 1Lab, 1P) Hours per semester 45 (15L, 15Lab, 15P)

Objectives of the

course

To provide up to date knowledge on methods and techniques used in acquisition,

processing and analysis of biosignals and to develop practical skills useful in this field.

Entry requirements/

prerequisites Mathematics, signal processing.

Course contents

Lectures: Biosignals: definitions, classification. Methods and techniques of biosignal

acquisition, processing and analysis. Biosignal analysis in time and frequency domain.

Chosen methods of statistical biosignal analysis. MATLAB and LabView environments in

biosignal processing and analysis, dedicated toolboxes.

Labs: Chosen biosignals analysis using software tools: MATLAB, LabView.

Project: Using computer tools in processing and analysis of biological signals, implementing

algorithms applied to different biosignals.

Assessment methods Written exam, accomplishment of practical labs and project work.

9

Learning outcomes

The student has knowledge on methods and techniques used in acquisition, processing and

analysis of biomedical signals as well as on research methodology used in this field. He has

practical skills useful in this area regarding bio-measurements (instrumentation, specialized

software tools).

Required readings

1. Bronzino J. D. (ed.): Biomedical Engineering Handbook, CRC Press, IEEE Press, 1995.

2. Oppenheim, A.V. and Schafer W.: Discrete-time signal processing, Prentice Hall, 1999.

3. Cohen L.: Time-frequency analysis, 1995.

4. Qian S., Chen D.: Joint time-frequency analysis. Methods and Applications, Prentice-Hall,

1996.

Supplementary

readings Eugene N. Bruce: Biomedical Signal Processing and Signal Modeling, Wiley, 2001.


Course title BIOMEDICAL TECHNOLOGY EQUIPMENT

Field of study

Teaching method lectures, labs (also in hospital)





Course code




Hours per week 1L/2Lab Hours per semester 15L/30Lab

Objectives of the

course

To provide basic knowledge on biomedical technology: instrumentation, equipment,

specialized systems, and to develop practical skills useful in this area of engineering.

Entry requirements/

prerequisites Mathematics, Physics, Informatics, fundamentals of semiconductor electronics.

Course contents

Lectures: Biomeasurements, biomedical instrumentation, biosignals (1-D, 2-D) acquisition.

Equipment: ECG, EEG, EMG, VEP/P300, biofeedback and neurofeedback system. Typical

medical imaging systems. Medical telematics, IT in e-Health. Computer aided medical

diagnosis. Assessment of biomedical devices and technologies.

Labs: Biosignals and biomeasurements. Biosignal acquisition, processing and analysis using

specialized transducers, amplifiers and equipment.

Assessment methods Lectures: grade, accomplishment of lab tasks.

10

Learning outcomes

The student has basic knowledge on biomedical technology (instrumentation, equipment,

software, specialized systems and standards used in this field). He has practical skills useful

in the area of biomedical technologies regarding their development, implementation,

exploitation and assessment.

Required readings

1. Bronzino J. D. (ed.): Biomedical Engineering Handbook, CRC Press, IEEE Press, 1995.

2. Bemmel, van J. H., Musen M. A.: Handbook of Medical Informatics, Bohn Stafleu Van

Loghum, Springer, 1997.

3. Christensen D. A.: Ultrasonographic Bioinstrumentation, J. Wiley & Sons, N.Y., 1988.

Supplementary

readings Huang H. K.: PACS in Biomedical Imaging. VCH Publ. Inc., N.Y., 1996.


Course title COMPUTER ANIMATION

Field of study Control Engineering & Robotics, Teleinformatics, Electronics & Telecommunications



the course

Przemysław Mazurek

Dr Eng Sc


person responsible for the

course

[email protected]

Course code


Type of course optional Level of course bachelor

Semester winter or summer Language of instruction english

Hours per week 2W 2L Hours per semester 30W, 30L

Objectives of the

course

Basic knowledge about 3D graphics and applications using software tools. Practical aspects

of computer animation.

Entry requirements/

prerequisites -

Course contents 3D modeling, 3D synthesis of objects, rendering techniques, lighting, textures, keyframe

animation, human body modeling and animation, morphing

Assessment methods

grade

training

project work

Learning outcomes Knowledge about: 3D computer animation , special effects, film production

Required readings Blender, e-on Vue, Adobe Photoshop tutorials

11

Supplementary

readings -


Course title COMPUTER GRAPHICS AND VISUALISATION

Field of study ICT

Teaching method Lecture + project


the course Krzysztof Okarma



Course code




Hours per week 2 Lecture / 2 project Hours per semester 30 Lecture / 30 project

Objectives of the

course

This course is intended to present fundamental algorithms in computer graphics as well as

some advanced techniques used in image synthesis

Entry requirements/

prerequisites

Fundamentals of computer engineering, mathematics (a short introduction to 3-D

geometry is provided)

Course contents

Digital image – classes, representations and conversion methods. Characteristics and

parameters of computer images. Raster and vector graphics. Methods of line drawing in

raster computer graphics. Bresenham’s algorithm. Polygon triangulation methods.

Techniques of area’s filling in raster images. Geometric operations on raster images in two-

dimensional and 3-D spaces. Visualisation of 3-D figures. Field of view. Virtual camera

model used in computer graphics. Algorithms for surfaces’ visibility detection. Depth buffer.

Texturing methods. Modelling of smooth shapes and surfaces. Applications of fractals in

computer graphics. Data structures used in computer graphics. Methods of colours’

representing (colour spaces). Graphic file formats. Basics of OpenGL standards –

specification and properties. 3-D images synthesis methods. Light modelling and shading

methods. Ray-tracing and radiosity methods in computer visualisation.

Assessment methods Written exam (test) / project work

Learning outcomes Knowledge of fundamentals of computer graphics. Ability to utilize some computer

graphics algorithms and/or applications for computer visualisation purposes.

Required readings

1. Foley J.D. et al: An Introduction to Computer Graphics. Addison-Wesley, 2000.

2. Pavlidis T.: Algorithms for Graphics and Image Processing, Computer Science Press,

Rockville, 1982

Supplementary

readings

1. Yun Q. Shi, Huifang Sun: Image and Video Compression for Multimedia Engineering -

Fundamentals, Algorithms and Standards.

12

CRC Press 2000.

2. Ling Guan, Sun-Yuan Kung, Larsen J.: Multimedia Image and Video Processing. CRC Press

2001.


Course title COMPUTER METHODS FOR MATHEMATICAL COMPUTATIONS

Field of study Electrical Engineering, Computer Engineering, Electronic Engineering, Information

Technology Engineering, Automation and Robotics Engineering

Teaching method Lectures, Laboratory


the course Marcin Ziółkowski



Course code


Type of course Obligatory Level of course Bachelor


Hours per week Lectures - 2

Laboratory - 2 Hours per semester

Lectures - 30

Laboratory – 30

Objectives of the

course

This course is intended to present a unified approach to various numerical methods in

Matlab environment.

Entry requirements/

prerequisites Mathematics

Course contents

1. Floating-Point Arithmetic

2. Linear Equations

3. LU Factorization

4. Effect of Roundoff Errors

5. Norms and Condition Numbers

6. Sparse Matrices and Band Matrices

7. PageRank and Markov Chains

8. Interpolation

9. Zeros and Roots

10. Least Squares

11. Curve Fitting

12. Quadrature

13. Ordinary Differential Equations

14. Fourier Analysis

15. Random Numbers

16. Eigenvalues and Singular Values

17. Inverse Problems in Engineering

Assessment methods Lectures – written exam; Laboratory – continuous assessment

Learning outcomes Students will get the knowledge about applying computer methods for solving

mathematical problems.

mailto:[email protected]

13

Required readings

1. S. Moler: Numerical Computing with Matlab, electronic edition, The MathWorks, Inc.,

Natick, MA, 2004

2. G. Forsythe, M. Malcom, C. Moler: Computer Methods for Mathematical Computations,

Prentice-Hall, Englewood Cliffs, NJ, 1977

Supplementary

readings Per Christian Hansen: Regularization Tools, Technical University of Denmark, Lyngby, 2008


Course title COMPUTER NETWORKS

Field of study ICT



the course Piotr Lech



Course code


Type of course obligatory Level of course bachelor


Hours per week 1 Lecture / 2 Lab. Hours per semester 15 Lecture /

30 Laboratory

Objectives of the

course

This course introduces the fundamental problems of computer networking, from sending

bits over wires to running distributed applications. Topics include error detection and

correction, multiple-access, bandwidth allocation, routing, internetworking, reliability,

quality of service, naming, content delivery, and security.

Entry requirements/

prerequisites Prerequisites and additional requirements not specified

Course contents

Introduction: to Network Models, Protocols and Layering, Physical and Link layers,

Retransmissions, Multiple access, Switching , Network layer, Internet working, Routing,

Internet protocol suite , Transport layer, Reliability , Congestion Control, DNS, Web/HTTP,

Content Distribution, Quality of Service and Real-time Apps Network Security , Client-server

and peer-to-peer architectures.

Assessment methods Written exam (test), continuous assessment (laboratory)

Learning outcomes

Knowledge of basic configuration of computer networks and IP networks .Addressing in

computer networks. Understanding of layered models in networking. Understanding of

protocols'

Required readings

1. Carla Schroder Linux Networking Cookbook O'Reilly Media 2007 ISBN: 978-0-596-

10248-7 Ciprian Adrian Rusen, 7 Tutorials Network Your Computers & Devices Step by

Step Microsoft Press 2010 ISBN: 978-0-7356-5216-3

14

Supplementary

readings Selected RFC documents.


Course title COMPUTER VISION AND IMAGE PROCESSING

Field of study ICT



the course Krzysztof Okarma



Course code





Objectives of the

course

This course is intended to present a unified approach to image processing techniques with

introduction to image analysis and basics of computer visualisation

Entry requirements/

prerequisites

Basic knowledge of Matlab or Mathcad environments,

basic knowledge about programming and signal processing

Course contents

Digital image – classes, representations and conversion methods. Colour models. Arithmetic

and logic operations on digital images. Geometric operations, matrix notation. Digital

image acquisition. Local processing and filtration using convolution filters. Methods for

reduction of the number of colours. Deformations, bilinear projection and morphing.

Frequency-based image processing methods. Histogram and histogram-based operations.

Binarization. Morphological operations. Image segmentation. Indexing techniques in image

processing. Measuring methods using image analysis. Lossy and lossless image

compression standards. Image and video quality assessment methods. Nonlinear filtration

of colour images. Basics of photogrammetry and 3D Vision. Applications of machine vision

in automation and robotics.


Learning outcomes Knowledge of basic image processing and analysis algorithms. Ability to implement some

image processing and basic image analysis algorithms in chosen environment (e.g. Matlab).

Required readings 1. Pratt W.K.: Digital Image Processing (4th Edition). Wiley Interscience, New York 2007.

15

Supplementary

readings

1. Foley J.D. et al: An Introduction to Computer Graphics. Addison-Wesley, 2000.

2. Pavlidis T.: Algorithms for Graphics and Image Processing, Computer Science Press,

Rockville, 1982.

3. Nelson M.: The Data Compression Book. IDG Books Worldwide, Inc. 2000.

4. Ritter G.X., Wilson J.N.: Handbook of Computer Vision - Algorithms in Image Algebra.

CRC Press 1996.

5. Russ J.C.: The Image Processing Handbook. CRC Press 1999.


Course title CONTROL OF ELECTRIC DRIVES

Field of study Electrical engineering, automatic control systems, industrial electronics, mechatronics,

robotics

Teaching method lecture / laboratory





Course code


Type of course Obligatory Level of course master


Hours per week 1L/2Lab Hours per semester 15 L /30 Lab.

Objectives of the

course

Student will recognize and distinguish basic properties and parameters of DC motors, will

be able to construct basic motor models. Will understand cascaded control systems, PI

controller operation and basics of controller tuning. Will have an overview of basic

properties of PM excited and series and parallel connected DC machines. Students will

recognize basic properties, characteristics and types of induction machines (IM and DFIG) as

well as types of controllers and control types for induction machines. Students will get

familiar with basics of frequency converter operation and parametrization. Students will

distinguish scalar and vector control. Students will recognize basic properties of permanent

magnet excited machines (PMSM and BLDC) and will be able to draw basic waveforms for

BLDC and PM type machines operation. Students will be able to set up a basic control type

(torque, speed) and frequency converter operation.

Entry requirements/

prerequisites

Basics of electrical engineering, electric machines, basics of automatic control, power

electronics

16

Course contents

Overview of basic types of DC machines: auxiallary excited, series and parallel connected.

Mechanical characteristics. DC machines: parameters, models. Automatic control rules,

controller types, basic definitions. Cascaded control: controller tuning using module and

symmetry criterion. Induction machines: construction (IM and DFIG), properties, control

types. Basic scalar control: types, voltage control, frequency control. Vector control: axis

transformation, voltage based control, Blaschke equations, current based methods.

Characteristics and basic properties of different constructions. Control system examples in

Matlab and using Simovert drives. PM excited machines: types, basic properties. BLDC

control systems, vector control strategies for PMSM motors. Drive systems for automobile

applications.

Assessment methods Written exam

Laboratory reports and written tests

Learning outcomes

Ability to calculate and analyze properties of torque, speed and position controller settings

in case of DC – based, Ac – based and PM – based drive systems. Ability to define and

analyze parameters of machines and construct a proper machine model. Practical abilities

on controller setting influence on drive properties, drive system parametrization, inverter

settings.

Required readings


2. Bimal Bose, Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-

088405-6

Supplementary

readings


Course title CONTROL OF MOBILE ROBOTS

Field of study Automatic Control and Robotics

Teaching method Laboratory course involving simulation of control algorithms for mobile robots, path

planning and experimental verification on wheeled mobile robots.


the course Adam Łukomski



Course code



Semester Winter or summer Language of instruction english

Hours per week 2h laboratory Hours per semester 30h laboratory

Objectives of the

course

The Student will learn to design and apply nonlinear control to a class of wheeled mobile

robots.

Entry requirements/

prerequisites Linear control, Dynamical systems

17

Course contents

This course covers basic modelling of mobile robots, kinematics and dynamics, nonlinear

control design, path planning and trajectory following. Experimental verification will be

done using a two-wheeled platform (unicycle-like) and miniature car-like robot.

Assessment methods Written exam (on last meeting), Continuous assessment during laboratory course

Learning outcomes Ability to create a kinematic and dynamic model of the mobile robot.

Ability to create, analyse and implement a model-based control system.

Required readings 1. Murray, Richard M., et al. A mathematical introduction to robotic manipulation. CRC

press, 1994.

Supplementary

readings 1. Slotine, Jean-Jacques E., and Weiping Li. Applied nonlinear control. Prentice-hall, 1991.


Course title DIGITAL TECHNIQUE

Field of study

Teaching method lectures, lab





Course code


Type of course compulsory Level of course bachelor



Objectives of the

course

To provide basic knowledge on digital circuit theory and design and to develop skills in

analysis, testing and designing digital circuits using product data sheets as well as

application notes.

Entry requirements/

prerequisites Mathematics, fundamentals of semiconductor electronics.

18

Course contents

Lectures: Number systems. Binary codes, BCD codes. Basics of binary arithmetic. Automata,

logic circuit, digital circuit – basic definitions. Boolean Algebra, fundamental theorems.

Switching (Boolean) functions, simplification, minimisation. Preparing logic functions with

gates, multiplexers and demultiplexers, ROMs, PLA modules. Digital logic circuit - overview,

comparison, development. Time-dependent circuits, multi-vibrators, generators. Flip-flops,

logic description. Fundamentals of digital functional blocks - modules (combinatorial and

sequential). Digital control system, logic description – algorithms. Basics of

microprogramming technique. Introduction to ASICs, PLD modules – classification,

development

Labs: Switching functions minimisation. Preparing logic functions with gates and different

modules. Logic gates testing (switching functions, static and dynamic characteristics). Flip-

flops, registers and counters testing. Testing time-dependent circuits, multi-vibrators,

generators. Testing arithmetic circuits. Testing memories, input circuits and digital displays.

Assessment methods Written exam, accomplishment of practical lab tasks.

Learning outcomes

The student has knowledge on digital circuit theory, methods and techniques of digital

circuit analysis and synthesis, as well as digital circuit design. He has skills in the field of

analysis, testing and designing digital circuits using product data sheets, application notes

as well as dedicated software tools.

Required readings

1. Beards P. H.: Analog and Digital Electronics. A First Course, II ed., Prentice Hall, 1991.

2. Nelson V. P., Nagle H. T., Carroll B. D., Irwin I. D.: Digital Logic Circuit Analysis and

3. Design, Prentice Hall, New Jersey, 1995.

Supplementary

readings 1. Burger P.: Digital Design. A Practical Course, John Wiley & Sons, New York, 1998.


Course title ELECTRIC POWER NETWORK

Field of study Electrical engineering

Teaching method Lecture/project


the course Michal Zeńczak



Course code


Type of course Obligatory/elective Level of course Bachelor


Hours per week 1/1 Hours per semester 15/15

Objectives of the

course

Knowledge: about structure and functioning of electric power networks in normal and fault

conditions.

Skills: of designing of overhead lines and basic calculation for wires.

19

Entry requirements/

prerequisites Basis of electrical engineering, mathematics, physics.

Course contents

Structure of electrical power network, requirements for networks, quality of energy, towers

and wires, current-carrying capacity of wires, HTLS wires, standards for designing of

overhead transmission lines, cable lines, environmental problems.

Assessment methods Project work, final test on the end of lectures.

Learning outcomes

Knowledge: Student has knowledge for analysis of functioning and designing of electrical

power network.

Skills: Student is able to design electrical power network.

Required readings

Supplementary

readings

1. Kiessling F., Nefzger P., Nolasco J.F., Kaintzy U.: Overhead Power Lines, Springer, 2002

2. Grainger J.J., Stevenson W.D.: Power System Analysis, McGAW-HILL

3. INTERNATIONAL EDITIONS, 1994,

4. Grigsby L.L.: The Electric Power Engineering Handbook, CRC PRESS, 1998,

5. Grigsby L.L.: Electric Power Generation, Transmission, and Distribution, CRC PRESS,

2007,

6. Saccomanno F.: Electric Power Systems, Analysis and Control, John Wiley&Sons, 2003,

7. Weedy B.M., Cory B.J.: Electric Power Systems, John Wiley&Sons, 1998,

8. Northcote-Green J., Wilson R.: Control and Automation of Electrical Power Distribution

Systems, Taylor&Francis, 2007


Course title ELECTRICAL CIRCUIT ANALYSIS WITH MATLAB


Technology Engineering






Course code


Type of course Obligatory Level of course Bachelor, Master




Lectures - 15

Laboratory – 30

Objectives of the

course

This course is intended to present a modern approach to electrical circuit simulation and

analysis using numerical method based on Matlab environment.


20

Entry requirements/

prerequisites Numerical Methods, Mathematics, Physics

Course contents

1. DC Analysis

2. Transient Analysis

3. Network Equations

4. Solution of Linear Algebraic Circuit Equations

5. Solution of Nonlinear Algebraic Circuit Equations

6. Solution of Differential Circuit Equations

7. Application to Circuit Simulation

8. Operational Amplifiers

9. Transistor Circuits


Learning outcomes Students will get the knowledge about electrical circuits’ simulations methods based on

network approach.

Required readings 1. John O. Attia: Electronics and circuit analysis using Matlab, CRC Press LLC, 1999

2. Farid N. Najm: Circuit simulation, A John Wiley & Sons, Inc, 2010

Supplementary

readings 1. Steven T. Karris: Circuit analysis with Matlab applications, Orchard Publications, 2003


Course title ELECTRICAL POWER ENGINEERING


Teaching method Lecture, laboratory, classes.


the course Michał Zeńczak



Course code


Type of course Obligatory/elective/

optional Level of course Bachelor


Hours per week 2/1/1 Hours per semester 30/15/15

Objectives of the

course

Knowledge about composition and operation of power system,

Skills of calculation in power system: load flows, short-circuits,

Skills of investigation of basic phenomena in power system.

Entry requirements/

prerequisites Basis of electrical engineering, mathematics, physics.

21

Course contents

Composition of power system, methods of generation of electrical energy, power stations,

equivalent diagrams, voltage loss and voltage drop, vector diagrams, load flow study,

power losses, control of active power and frequency, control of voltage and reactive power,

basic interferences in power system, calculation of load flow study, calculation of voltage

losses and drops, calculation of short-circuits currents, measurements of currents and

voltages in power system, measurements of voltage drops, investigation of radial networks,

investigation of voltage control in power system, investigation of short-circuits,

investigation of non-homogeneous network.

Assessment methods Continuous assessment in laboratory, final test on the end of classes and lectures

Learning outcomes

Knowledge:

Student has knowledge for understanding processes of generation of electrical energy,

Student has knowledge for basic calculation in power system,

Skills:

Student is able to calculate different state in power system.

Required readings

Supplementary

readings

1. Freris L., Infield D.: Renewable Energy in Power Systems, John Wiley&Sons, 2008,





2007,






Course title ELECTROMAGNETIC FIELD AND THE HUMAN BODY


Teaching method Lectures, laboratory – computer simulations


the course

Stanisław Gratkowski,

Katarzyna Cichoń

(lab – Krzysztof Stawicki)



the course

[email protected];

[email protected]

([email protected])

Course code


Type of course Optional Level of course Bachelor/master


22

Hours per week 2L/1 Lab, other

organization is possible Hours per semester 30L/15Lab

Objectives of the

course

To provide up to date knowledge on analysis and modeling of EM fields in the human body,

and to develop practical skills in this area

Entry requirements/

prerequisites Mathematics, physics

Course contents

Basic concepts of electric and magnetic fields; Maxwell’s equations; electromagnetic waves;

dosimetry; numerical modeling of electromagnetic field in the human body; magnetic

induction tomography and magnetoacoustic tomography with magnetic induction for

biomedical applications; examples of medical applications of electromagnetic fields;

biological effects of electromagnetic fields; magnetic resonance imaging (MRI)

Assessment methods Lectures – written and oral exam; laboratory (computer simulations) – continuous

assessment

Learning outcomes On successful completion of this course students will have knowledge on methods for

analysis and modeling of EM fields in living systems and practical skills useful in this area.

Required readings

1. Durney C.H.: Basic Introduction to Bioelectromagnetics. CRC Press LLC, Boca Raton 2000

2. Sadiku M.N.O.: Numerical Techniques in Electromagnetics. CRC Press LLC, Boca Raton

2001

3. IEEE Transactions on Biomedical Engineering

4. Malmivuo J., Plonsey R.: Bioelectromagnetism. Oxford University Press, New York 1995

Supplementary

readings


Course title ELECTROMAGNETIC METHODS OF NON-DESTRUCTIVE TESTING

Field of study Electrical engineering, Mechanical engineering, Automatics

Teaching method Lecture and experimental laboratory


the course

Tomasz Chady

Przemysław Łopato

Grzegorz Psuj



Course code




Hours per week 3L / 2Lab Hours per semester 45L / 30Lab

Objectives of the

course

To give basic knowledge of techniques for non-destructive testing (NDT),

To teach how to apply specific method in practical applications,

To give students an understanding of NDT by comparing the major evaluation


23

methods,

To introduce modern systems and techniques for NDT

Entry requirements/

prerequisites

Academic course of mathematics and physics (required)

Academic course of electrotechnics (suggested)

Course contents

Non-destructive testing - the introduction, the basic idea, the historical background

Review of different methods of non-destructive testing

Transducers for measuring magnetic fields

Non-destructive testing using Barkhausen noise

Method of flux leakage

Eddy current method

Evaluation of low conductivity materials using electromagnetic waves of high frequency

(THz – terahertz TDS imaging)

Computer and digital radiography

Numerical modeling in NDT

The algorithms of digital signal processing in NDT

Algorithms for identification in NDT

Data fusion algorithms

Computer systems in NDT

Industrial tomography

Overview of commercial non-destructive testing systems

Overview of standards used in NDT

Laboratory experiments for selected topics.

Assessment methods Written exam (Lect.) + Continuous assessment (Lab)

Learning outcomes

Upon successful completion of the course, the student will be able to:

identify, formulate, and solve engineering problems in the field of NDT,

explain the principles of the major NDT methods,

identify advantages and limitations of nondestructive testing methods and to select the

appropriate techniques for inspections in specific application,

use selected software for numerical modelling of NDT systems,

use selected hardware for practical NDT (i.e. THz TDS or digital detectors for X-ray

testing,

critically evaluate their chosen problem solving techniques and the accuracy of their

answers.

Required readings 1. Hellier C. J., Handbook of Nondestructive Evaluation, McGrown-Hill, 2003

Supplementary

readings

1. Blitz. J., Electrical And Magnetic Methods of Non-Destructive Testing, Springer-Verlag,

1997

2. Mester M. L., McIntire P, Nondestructive Testing Handbook Volume 4 Electromagnetic

Testing, ASNT, 1996

3. Jiles D. C., Introducting to Magnetism and Magnetic Materials, Springer, 1990

4. Sakai K., Terahertz Optoelectronics, Springer-Verlag Berlin Heidelberg 2005

5. Tumanski, S., Principles of electrical measurement, Taylor & Francis Group, 2006

Additional information Maximum number of students in case of the laboratory group: 10

24

Course title ELECTRONIC DEVICES AND CIRCUITS

Field of study

Electronics and Telecommunications

Automatic Control and Robotics

Electrical Engineering

Teaching method lectures, lab


the course Witold Mickiewicz



Course code


Type of course Compulsory / optional Level of course bachelor



Objectives of the

course

To provide knowledge on electronic semiconductor devices selected topics on analog

electronic circuits.

Entry requirements/

prerequisites Mathematics, physics.

Course contents

Lectures:

Conduction in semiconductors. Semiconductor-diode characteristics. BJT characteristics.

Transistor biasing and thermal stabilization. Small-signal low-frequency transistor model.

Low-frequency transistor amplifier circuits. The high-frequency transistor. Field-effect

transistors. Integrated circuits. Operational amplifiers. Feedback amplifiers and oscillators.

Active filters circuits. Large-signal amplifiers. Optoelectronics devices. Rectifier and power

supplies.

Labs:

Static and dynamic characteristics of diodes and transistors. Bipolar transistor biasing and

stabilization of operating point. Transistor amplifiers. Applications of operational amplifiers.

Active filters. Oscillators. Rectifiers. Electronic voltage regulators. DC voltage stabilizers.

Assessment methods Written exam, accomplishment of practical lab tasks.

Learning outcomes

The student has knowledge on basic electronic devices and circuit, methods and techniques

of analog circuit analysis. He has skills in the field of analysis, testing and designing simple

electronic circuits using product data sheets, application notes as well as dedicated software

tools.

Required readings 1. Boylestad R.L., Nashelsky L.: Electronic devices and circuit theory, Eleventh edition,

Pearson 2013.

Supplementary

readings 1. Roland E. Thomas: The Analysis and Design of Linear Circuits, 7th Edition, Wiley 2012


25

Course title ELEMENTS OF LASER OPTICS

Field of study Electronics and Telecommunications, Teleinformatics, Automatic Control and Robotics,


Teaching method Lecture + Laboratory


the course Dr Andrzej Ziółkowski



course

[email protected]

Course code

(if applicable)

ECTS points 3

Type of course facultative Level of course master

Semester summer Language of instruction English

Hours per week 1h-lecture, 1h-project Hours per semester 15h—lecture

15h-project

Objectives of the

course

The first objective of this course is to give basic optics and photonics concepts related to

laser physics.

Entry requirements/

prerequisites Basics knowledge in mathematics and physics

Course contents

Elements of laser optics: Topics related to the basics of laser physics. In particular issues

related to the absorption and emission of light, laser linewidth, pumping processes, optical

amplifiers and optical resonators. Moreover, we will discuss construction and operation of

selected types of lasers such as: gas lasers, semiconductor lasers, solid state lasers.

Assessment methods Lecture, laboratory and numerical simulations

Learning outcomes At successful completion of this course the students will be familiar with main properties of

lasers and other optoelectronic devices

Required readings

1. William T. Silfvast, Laser Fundamentals, Cambridge University Press, 2004

2. E. Rosencher, B. Vinter, "Optoelectronics", Cambridge Univ. Press, Cambridge 2002

3.B. E. A. Saleh, M. C. Teich, Fundamentals of Photonics, Wiley Series in Pure and Applied

Optics, 2007

Supplementary

readings


Course title ELEMENTS OF PSYCHOACOUSTICS AND ELECTROACOUSTICS

Field of study Electronics and Telecommunications, Automatic Control and Robotics, Electrical Engineering

Teaching method lectures, seminar, laboratory

26





Course code


Type of course optional Level of course bachelor, master

Semester winter or summer Language of instruction english

Hours per week 1L/1S/2Lab Hours per semester 15L/15S/30Labs

Objectives of the

course

To provide knowledge on psychoacoustics basics and selected topics on electroacoustics

(sound fields, transducers, sound reinforcement, sound processing).

Entry requirements/

prerequisites Basic knowledge in Physics

Course contents

Lectures: Sound waves properties. Human auditory system. Musical sounds, notes and

harmony. Elements of psychoacoustics – monaural and binaural hearing effects. Spatial

hearing. Fundamentals of room acoustics and perceiving sound in different environments.

Elements of building acoustics. Electroacoustical transducers and electroacoustical systems.

Hearing aids. Digital sound processing. Audio compression. HRTF technology and 3-D

audio systems.

Seminar: complementary calculation exercises

Labs: Models of human auditory system. Experiments in hearing. Hearing aids, software

support. MATLAB in processing, compression and enhancement of audio signal. 3-D audio

enhancements of 2-channel sound. Loudspeaker parameters identification. Microphones

parameters measurement. Reverberation time measurement. Sound isolation measurement.

Filtering, sound effects.

Assessment methods Written exam, accomplishment of practical labs

Learning outcomes The basic knowledge on psychoacoustics and selected topics on acoustics and

electroacoustics. The skills to use and measure basic electroacoustical systems.

Required readings 1. Howard D. H.: Acoustics and psychoacoustics. Focal press, 2001.

2. Everest F. A.: Master handbook of acoustics. McGraw-Hill, 2001.

Supplementary

readings

1. Blauert J.: Spatial Hearing - Revised Edition: The Psychophysics of Human Sound

Localization. MIT Press, 1999.


Course title EM FIELDS EFFECTS IN LIVING ORGANISMS


Teaching method Lecture/laboratory





/exec/obidos/ASIN/0262024136/ref=sib_rdr_dp/002-4066478-7484004


27

Course code


Type of course Optional Level of course Master

Semester Winter Language of instruction English


Objectives of the

course

To provide up to date knowledge on bioelectromagnetism, electromagnetic fields in natural

environment and interaction of living systems with electromagnetic fields. To develop skills

in designing of electric power engineering structures according to standards for

electromagnetic fields in natural and occupational environment.

Entry requirements/

prerequisites Mathematics, physics, theoretical engineering, theory of electromagnetic fields.

Course contents

Basis of theory of electromagnetic fields in application for biology, natural

and technical sources of electromagnetic fields, standards for electromagnetic fields,

electrical properties of living master, electromagnetic fields inside living systems,

mechanism of interaction of non-ionising electromagnetic fields with living systems,

measurements of EM fields, computer simulations in EM fields, designing electric power

engineering structures according to standards for EM fields.

Assessment methods Continuous assessment in laboratory, final test on the end of lectures

Learning outcomes

Knowledge:

Student has knowledge on bioelectromagnetism, electromagnetic fields in natural

environment and interaction of living systems with electromagnetic fields,

Skills:

Student is able to design electric power engineering structures according to standards for

electromagnetic fields in natural and occupational environment.

Required readings

Supplementary

readings

1. Bronzino J.D., Biomedical Engineering Handbook, CRC Press, IEEE Press,, New York, 1995

2. Carstensen E., Biological effects of transmission line fields, Elsevier, New York,

Amsterdam, London, 1987

3. Malmivuo J., Plonsey R., Bioelectromagnetism, Oxford University Press,, Oxford, 1995

4. Polk C., Postow E., CRC Handbook of biological effects of electromagnetic fields, CRC

Press, Boca Raton, Florida, 1986

5. Wadas R.S., Biomagnetism, PWN, Warsaw, 1978


Course title FIBER OPTIC ACCESS NETWORKS (FOAN)

Field of study Electronics and Telecommunications, Electrical Engineering, Teleinformatics

Teaching method Lecture, Project and Seminar

28


the course

Dr Patryk Urban

(Dr Grzegorz Żegliński)



the course

[email protected]

([email protected])

Course code


Type of course Facultative / Optional Level of course Master

Semester Summer Language of instruction English

Hours per week 2h – Lecture/Seminar

2h – Project Hours per semester

30h – Lecture/Seminar

30h – Project

Objectives of the

course

The primary objective of this course is to obtain fundamental knowledge on FOAN design

rules and factors influencing decisions along the design process. This is to be preceded by

getting familiar with FOAN components as well as architectural and topological options for

FOANs.

The secondary objectives of this course are: to understand the economics of FOANs; to get

familiar with various relevant job profiles through face-to-face networking with

professionals in the field of optical access networks; to exercise students’ presentation skills

by orally reporting their project results.

Entry requirements/

prerequisites

Academic courses: Math, Physics. Moreover, it is recommended that course participants are

familiarized with the basics of fiber optics e.g. through attending the course Fiber Optics

Installation or alike. Although, essentials with this respect will be recalled during the course.

Course contents

1. FOAN Applications: Drivers and Business Needs

2. Bandwidth Requirements in Access Networks and Evolution of Access Networks

3. Generic FOAN Network Planning

4. FOAN Economics and Its Impacts onto FOAN Design

5. FOAN Terminology, Fiber Optic Symbols and FOAN-related Standards

6. Access Network Architectures and Transmission in FOAN

7. Passive Optical Network Essentials and Next Generation FOAN Outlook

8. FOAN Topologies, Components, Subsystems and Devices

9. FOAN Node Positioning

10. FOAN Network Design

Optional: Fiber-To-The Building Design Deep-dive

11. Loss Budget and Passive Optical Network Class

Assessment methods Project report and presentation (seminar)

Learning outcomes

After successful completion of the course, students will possess solid foundation to develop

towards professional in optical access networks. The students will be familiarized with

optical access network architectures, network components, as well as network planning and

designing. It will ensure students’ up-to-date knowledge base with current standards and

standardization projects under development as well as relevant technology roadmaps.

Required readings FTTH Handbook,

http://www.ftthcouncil.eu/documents/Publications/FTTH_Handbook_V7.pdf

Supplementary

readings

1. FTTH Council online resources, http://www.ftthcouncil.eu/resources/key-

publications

2. K. Wang et al., Techno-Economic Analysis of Active Optical Network Migration

Towards the Next Generation Optical Access, IEEE/OSA Journal of Optical

Communications and Networking, vol. 9, no. 4, April 2017, pp. 327-341

3. P. J. Urban et al., Fiber Plant Manager: an OTDR- and OTM-based Passive Optical

Network Monitoring System, IEEE Communications Magazine, vol. 51, no. 2,

February 2013, pp. 9-15


Optionally, a couple of visits to local companies involved in fiber optic access networks

businesses will be organized. Moreover, depending on availability, a couple of professionals

from local companies will be invited for guest presentations and discussion on their job

profiles.



http://www.ftthcouncil.eu/documents/Publications/FTTH_Handbook_V7.pdf

http://www.ftthcouncil.eu/resources/key-publications

http://www.ftthcouncil.eu/resources/key-publications

29

Course title FIBER OPTICS INSTALATION

Field of study Electronics and Telecommunications , Automatic Control and Robotics, Electrical

Engineering , Teleinformatics

Teaching method Lecture + Laboratory


the course Dr Grzegorz Zeglinski



course

[email protected]

Course code

(if applicable)

ECTS points 3



Hours per week 1h-lecture,

2h-laboratories Hours per semester

15h—lecture

30h-laboratories

Objectives of the

course

The first objective of this course is to give basic

concepts relating to optical fiber installations, designing and measurements.

Entry requirements/

prerequisites

Course contents

1. Fiber Optic Transmission

2. Optical Fiber Characteristic

3. Fiber Optic Cables

4. Fiber Splicing

5. Optical Fiber Connectors

6. Optical Fiber Spliters and Couplers.

7. Budget Of Optical Fiber Line.

8. Fiber Optic Light Sources

9. Fiber Optic Detectors and Receivers

10. Cable Installation and Hardware.

11. Optical Time Domaind Reflectometry.

12. Optical Fiber Telecommunicaion Standards.

13. Optical Spectrum Measurements.

14. Chromatic and Polarization Dispersion Measurements

15. Fiber Optics Instalation Documentation.

Assessment methods Lecture, laboratory and numerical simulations

Learning outcomes

At successful completion of this course the students will be familiar with application of

optical fiber measurement methods to instalation problem solving, application of

instalation techniques, tools and resources, calculate the system bandwidth, budget Of

optical fiber line noise, probability of error and maximum usable bit rate of a telecom fibre

system.

Required readings 1. Govind P. Agrawal - Fiber-Optic Communication Systems Third Edition

2. Optical Fiber Communications by: G. Keiser; 3rd edition

30

Supplementary

readings


Course title FUNDAMENTALS OF ENGINEERING ELECTROMEGNETICS


Teaching method Lectures with simple experiments, laboratory – computer simulations


the course

Stanisław Gratkowski

(lab – Krzysztof Stawicki)



the course

[email protected]

([email protected])

Course code




Hours per week 2L/2Lab, other

organization is possible Hours per semester 30L/30Lab

Objectives of the

course

Students will learn mathematical and engineering principles that enable them to

understand forces, fields, and electromagnetic waves; know how devices work that use

those principles and phenomena; and be familiar with the historical context in which

development of knowledge and devices occurred.

Entry requirements/

prerequisites

Mathematics (a knowledge of vector calculus is helpful, but not necessary, since a short

introduction to vectors is provided); physics

Course contents

Electromagnetic field concept. Vector analysis. Electrostatics: Coulomb’s law, Gauss’s law

and applications, electric potential, electric dipole, materials in an electric field, energy and

forces, boundary conditions, capacitances and capacitors, Poisson’s and Laplace’s

equations, method of images. Steady electric currents: current density, equation of

continuity, relaxation time, power dissipation and Joule’s law, boundary conditions. Static

magnetic fields: vector magnetic potential, the Biot-Savart law and applications, magnetic

dipole, magnetic materials, boundary conditions, inductances, magnetic energy, forces and

torques. Time-varying electromagnetic fields: Faraday’s law, Maxwell’s equations, time-

harmonic fields, Poynting’s theorem, applications of electromagnetic fields. Plane wave

propagation: plane waves in lossless media, plane waves in lossy media, polarization of

wave. Computer aided analysis of electromagnetic fields.

Assessment methods Lectures – written and oral exam; laboratory – continuous assessment

31

Learning outcomes

On successful completion of this course:

Students will be familiar with the different vector operators used in Maxwells’ equations

Students will be able to describe and understand the basic concepts underpinning

electricity and magnetism such as potential and field

Students will have an understanding of Maxwell’s equations

Students will be able to select the most appropriate laws/theorems/ solution techniques for

electromagnetic field analysis

Required readings

1. Cheng D. K.: Fundamentals of Engineering Electromagnetics. Addison-Wesley

Publishing Company, Inc., New York 1993

2. Pollack G. L., Stump D. R.: Electromagnetism. Addison Wesley Publishing Company, Inc.,

New York 2002

3. Stewart J. V.: Intermediate Electromagnetic Theory. World Scientific Publishing Co. Pte.

Ltd., London 2001

4. Chari M. V. K., Salon S. J.: Numerical Methods in Electromagnetism. Academic Press, San

Diego 2000

Supplementary

readings


Course title FUNDAMENTALS OF WEB DEVELOPMENT

Field of study ICT



the course Przemyslaw Włodarski



the course

[email protected]

Course code


Type of course Optional Level of course Bachelor


Hours per week 2 lect. / 2 proj. Hours per semester 30 lect. / 30 proj.

Objectives of the course This course is intended to present a set of technologies that enable creation of the fully

functional web page, working seamlessly on mobile, tablet and large screen browsers.

Entry requirements/

prerequisites Some programming experience (helpful but not necessary)

Course contents

Web page design blocks: HTML5 and CSS3 (syntax, images, hyperlinks, tables, multimedia,

etc.). Box model, positioning. Essential components of JavaScript (variables, arrays, loops,

functions) as well as JQuery (chaining, DOM elements, ajax, plugins). Server-side scripting

languages (PHP, Python): dynamic content, form processing, file handling, objects. Design

and implementation of database for web projects using MySQL (keys, data types, privileges

system). Interacting with file system, generating images, session control, user authentication

and personalization, responsive design.

32

Assessment methods Written exam (test), project work

Learning outcomes Knowledge of web development basics, including front-end as well as back-end side. Ability

to create web pages from scratch.

Required readings

1. Welling L., Thomson. L.: PHP and MySQL Web Development, 4th Edition, 2009.

2. Duckett J.: JavaScript and JQuery: Interactive Front-End Web Development, 1st Edition,

2014.

Supplementary

readings

1. Ducket J.: Web Design with HTML, CSS, JavaScript and jQuery Set 1st Edition, 2014.

2. Flanagan D.: JavaScript: The Definitive Guide: Activate Your Web Pages, 2011.


Course title HIGH VOLTAGE ENGINEERING

Field of study High Voltage Engineering, Electrical Engineering

Teaching method lecture / laboratory


the course Szymon Banaszak



Course code


Type of course Compulsory

Level of course bachelor


Hours per week 2 Lecture / 2 Lab Hours per semester 30 Lecture / 30Lab

Objectives of the

course

The aim of the subject is to acquaint students with high voltage technology, especially with

phenomena related to high voltages, construction of insulation systems, methods of

preventing or generating discharges, lightning and surge protection.

Entry requirements/

prerequisites

It is necessary to have basic information in the field of physics, electrical engineering,

material engineering.

Course contents

The course is based on the following points:

- economic issues of high voltage application,

- electric fields in various electrodes setups,

- practical applications of high voltage,

- dielectric strength and discharge development mechanisms in

vacuum/gas/liquids/solids,

- electric discharges, lightnings and protection against them,

- high voltage metrology and testing.

Assessment methods - written and oral exam (lecture),

- grade (laboratory)

33

Learning outcomes

Student gains knowledge on high voltage engineering including economic issues of high

voltage application, practical applications of high voltage and high voltage metrology and

testing.

Student is able to use methods and devices for measurement of high voltages, for proper

operation and development of high voltage insulation systems, knows safety precautions in

high voltage engineering.

Required readings E. Kuffel, W. S. Zaengl, J. Kuffel: High voltage engineering: fundamentals, Newnes (An

imprint of Elsevier), 2004

Supplementary

readings

1. M.S. Naidu, V. Kamaraju: High Voltage Engineering, Tata McGraw-Hill, 2009

2. H.M. Ryan: High Voltage Engineering and Testing, 2nd edition, The Institution of Electrical

Engineers, 2001


Course title INDUSTRIAL ELECTRONICS PHD RESEARCH LAB


robotics

Teaching method Lab work / classes





Course code


Type of course Obligatory Level of course doctoral


Hours per week 8 (6 Lab, 2 Classes) Hours per semester 120 (90 Lab, 30 Classes)

Objectives of the

course

To provide knowledge on research methodology, design methods and techniques, project

management, and to develop various skills useful in solving complex problems in the field

of power electronics, drive systems, embedded controller design.

Entry requirements/

prerequisites

Electrical engineering, basics of power electronics, basics of automatic control, drive

systems, microcontroller technology

Course contents

Individual research work on topics concerning interdisciplinary engineering and scientific

problems of the thesis. The specific topics are specified by the students at the beginning of

the semester, during consultation meetings; the topics may be also proposed by the

students. Research work is performed using Chair of Electrical Engineering and Drives

infrastructure, including labs, equipment, computers & software, Internet access, library,

copying facilities etc. Tutorials with supervisor – person involved in running all the project

topics – are carried out regularly during the whole semester, with presentation of the

progress in research work in the mid of semester, in a form of

a seminar open for all students and teachers. Final assessment of the project work is made

on the basis of evaluation of the progress by the supervisor and of oral presentation during

the second, final seminar (also open for all interested persons). Topics of research are to be

related to:


34

Power electronics simulation, design and construction

Industrial electronics

Drive control systems and algorithms

CAD design of power electronic prototypes

Prototype construction and testing

Embedded control systems for power electronics and industrial control

Complex analysis of industrial systems

Assessment methods Continuous assessment of lab and project work, evaluation of the oral presentation of the

project results during the final seminar

Learning outcomes

The student has knowledge on research and design methodology, and on performing

project work. He has practical skills useful in solving interdisciplinary problems in the field of

electrical engineering and industrial electronics.

Required readings

1. M. H. Rashid Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-7

2. Bimal Bose Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-

088405-6

3. K. Billings, T. Morey Switching power supply design, ISBN 978-0-07-148272-

1McGrawHill 2009

4. K. Billings Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill

1999

Supplementary

readings


Course title INTRODUCTION TO CONTROL ENGINEERING

Field of Study

Automatic control and robotics; Electronics and telecommunication;

Information and communications technology;

Electrical engineering.

Teaching method Lectures, demonstrations, laboratory exercises


the course Paweł Dworak



Course code




Hours per week 1L, 2Lab Hours per semester 15L, 30Lab

Objectives of the

course Ability of the analysis and design techniques of control systems.

Entry requirements

/prerequisites Basics knowledge of physics, mathematics and signal processing

Course contents Control history and state of the art. Classification of control systems. Principles of automatic

35

control. Closed loop systems. Feedback systems. Transfer function approach Determination

of transfer functions for simple systems. Characteristics of basic elements and elementary

systems. Frequency response representation – frequency domain specifications. Steady

state response – steady state error- static & dynamic error coefficients. Stability of linear

systems. Introduction to design – compensation techniques – P, PI, PD and PID control. Gain

scheduling, fuzzy logic, neural networks in control engineering.

All problems are validated with the use of the Matlab-Simulink.

Assessment methods Continuous assessment, laboratory reports.

Learning outcomes Students will be able to analyze a simple process and design the control loops.

Required readings Any book on control system design, feedback systems, linear control systems. Some

examples are listed as supplementary readings.

Supplementary

readings

1. Aström K.J.: Control System Design, 2002.

http://www.cds.caltech.edu/~murray/courses/cds101/fa02/caltech/astrom.html

2. Aström K.J., Murray R.M.: Feedback Systems: An Introduction for Scientists and

Engineers. http://www.cds.caltech.edu/~murray/amwiki/index.php/Main_Page

3. Coughanowr D.R.: Process systems analysis and control. McGraw-Hill, Inc., 1991.

4. Dorf R.C., Bishop R.H.: Modern Control Systems, Prentice Hall, 2001.

5. Doyle J., Francis B., Tannenbaum A.: Feedback Control Theory. Macmillan Publishing

Co., 1990.

6. Goodwin G., Graebe S.F., Salgado M.E.: Control System Design,. Prentice Hall, 2001.

7. Powell F., Naeini E.: Feedback Control of Dynamic Systems. Prentice Hall, 2002.

8. Rowland J.R.: Linear Control Systems. Modelling, analysis, and design. John Wiley,

New York, 1986 .

9. de Silva C.W.: Modeling and control of engineering systems. CRC Press, New Jersey,

2009.


Course title INTRODUCTION TO CRYPTOGRAPHY

Field of study ICT

Teaching method lecture, written homework, labs


the course Maciej Rafał Burak



Course code




Hours per week 1 lecture / 2 lab Hours per semester 15 lecture / 30 lab

Objectives of the

course

This course explains the workings of basic cryptographic primitives and how to use them in

real world applications.


36

Entry requirements/

prerequisites

The course is self contained, however basic knowledge of probability theory will be helpful.

In order to complete the labs, basic programming knowledge is required (preferably in the

C language).

Course contents

Overview and history of cryptography. Vigenere (XOR) and Vernam (OTP) ciphers. Perfect

security. Block ciphers, modes of operations, semantic security. Stream ciphers.

Cryptographic hash functions, passwords and their weaknesses, brute force dictionary

attacks, salt. Data integrity, authenticated encryption. Key management and distribution.

Public key systems, certificates. SSL/TLS.

Assessment methods final (written) test, written homework, lab protocols

Learning outcomes Students will learn how to choose and apply cryptographic techniques to real-world

applications.

Required readings

Supplementary

readings

1. Menezes, van Oorschot and Vanstone. The Handbook of Applied Cryptography

2. Dan Boneh, Victor Shouph. A Graduate Course in Applied Cryptography

3. William, Stallings. Cryptography and Network Security

4. Ross Anderson. Security Engineering


Course title INTRODUCTION TO ELECTRIC CIRCUITS 1


Teaching method Lecture, practical exercises and experimental laboratory


the course

Tomasz Chady

Przemysław Łopato

Grzegorz Psuj

Krzysztof Stawicki



Course code




Hours per week 2L / 1Practical / 2Lab Hours per semester 30L / 15Practical /

30Lab

Objectives of the

course

To teach students basics of electrical circuit theory

To give students an understanding of the laws governing the behavior of electrical

circuits, and the ability to apply this understanding to the direct current and sinusoidal

steady-state circuit analysis

To give students an understanding of the analysis and design of common circuits

Entry requirements/

prerequisites Academic course of mathematics and physics


37

Course contents

Introduction and electric circuit variables (Definitions, Units, Types of signals, Circuits

and current flow, units, voltage, power and energy)

Circuit elements (linear model, active and passive elements, independent and

dependent elements)

Resistive circuits (resistors, Ohm and Kirchhoff’s law, basic circuit analysis)

Circuit theorems (superposition, substitution, fitting, Thevenin’s and Norton’s theorem)

Circuit analysis (nodal analysis, mesh analysis )

Energy storage elements (inductors, capacitors)

Sinusoidal steady-state analysis (classical method, phasor method, circuit law in phasor

method)

Ideal and real resonance, frequency characteristics


Assessment methods Written exam (Lect.) + Continuous assessment (Practical, Lab)

Learning outcomes


think analytically and creatively to draw conclusions and solve problems,

apply Ohm's and Kirchhoff's laws to solve for unknown voltage and/or currents

simplify series and parallel combinations of passive and active elements

use nodal analysis to write simultaneous equations

use mesh analysis to write simultaneous equations

apply superposition to linear circuits analysis

use Thevenin / Norton equivalent circuits to analyze circuits linear and selected

nonlinear circuits

analyze steady state sinusoidal circuits using the advanced circuit analysis techniques

(phasor method)

use phasor diagrams to visualize responses of the circuits

analyze RLC circuits in case of resonance

use basic instruments to measure voltages and currents

identify and apply the most appropriate circuit analysis technique

Required readings 1. W.H. Hayt, J.E. Kemmerly: Engineering circuit analysis, McGraw-Hill Book Company,

ISBN 0-07-027393-6

Supplementary

readings

1. Charles K. Alexander and Matthew N.O. Sadiku: Fundamentals of Electric Circuits, 2nd

Edition, , 4th Edition, McGraw-Hill, 2009

2. J.O. Attia: Pspice and Matlab for Electronics, CRC Press 2002, ISBN 0-8493-1263-9


Course title INTRODUCTION TO ELECTRIC CIRCUITS 2


Teaching method Lecture and experimental laboratory


the course

Tomasz Chady

Przemysław Łopato

Grzegorz Psuj

Krzysztof Stawicki




38

Course code





Objectives of the

course

To give students an understanding of the laws governing the behavior of electrical

circuits, and the ability to apply this understanding to the advanced methods of circuit

analysis in a steady and transient state

To give students an understanding of the analysis and design of common circuits in a

steady and transient state

To teach students how to use computer simulators for circuits analysis

Entry requirements/

prerequisites

Academic course of mathematics and physics

Academic course: Introduction to electric circuits 1

Course contents

Three phase circuits (symmetric Y and triangular, unsymmetrical circuits, power, reactive

power compensation)

Self and mutual inductance (ideal and with ferromagnetic core transformers)

Transient phenomena (DC and AC circuits)

The Laplace transformation (direct and inverse transformation)

Analysis of complex circuits in the transient state

The amplifiers (the operational and ideal operational amplifier)

Two-port’s (passive, active, equations, T and Pi scheme, A, A-1 Y, Z, h, g parameters,

relationship between parameters, interconnection of two port networks)

Fourier series (formulas, spectrum, power, compensation reactive power)

Digital transformation (Nyquist’s formula, Shannon’s formula)

Filters ( passive, active and digital)

Computer simulators for circuit analysis (SPICE)


Assessment methods Written exam (Lect.) + Continuous assessment (Lab)

Learning outcomes


think analytically and creatively to draw conclusions and solve problems,

identify, formulate, and solve engineering problems

analyze steady state sinusoidal three phase circuits,

use phasor diagrams to visualize responses of the three phase circuits,

analyze transient state in the first and second order RLC circuits by solving the

differential equations and using the Laplace transform.

identify and apply the most appropriate circuit analysis technique,

know the characteristics of the opamp,

use opamps in order to achieve the desired function,

use Fourier series to analyze circuits with no sinusoidal sources,

use the two port networks,

design passive and active filters with desired characteristics,

use computer simulators (SPICE) for numerical circuit modelling and analysis,

critically evaluate their chosen problem solving techniques and the accuracy of their

answers.

Required readings 1. W.H. Hayt, J.E. Kemmerly: Engineering circuit analysis, McGraw-Hill Book Company,

ISBN 0-07-027393-6

39

Supplementary

readings

1. Charles K. Alexander and Matthew N.O. Sadiku: Fundamentals of Electric Circuits, 2nd

Edition, , 4th Edition, McGraw-Hill, 2009

2. J.O. Attia: Pspice and Matlab for Electronics, CRC Press 2002, ISBN 0-8493-1263-9


Course title INTRODUCTION TO MULTISENSOR DATA FUSION

Field of study Electrical engineering and computer engineering

Teaching method Lectures with simple cases presentations, project – design and implementation of data

fusion algorithm


the course Grzegorz Psuj



Course code


Type of course obligatory Level of course bachelor/master


Hours per week 1 L / 1 P Hours per semester 15 L/15 P

Objectives of the

course

This course is intended to present an introduction to the multisensor data fusion concept

and theory followed by the case study.

Entry requirements/

prerequisites

Academic course of mathematics and informatics. Basics of programming in

Matlab/Octave/SciLab or other similar environment.

Course contents

1. Introduction: motivation, concepts and theory of data fusion.

2. Data fusion models and architectures.

3. Sensors types.

4. Levels of data fusion.

5. Data registration: concepts and theory, algorithms partition and basic description,

examples.

6. Data fusion algorithms: concepts and theory, algorithms partition and basic

description.

7. Quality assessment factors of performance evaluation.

Case study of data fusion applications.

Assessment methods Lectures – exam; project – report assessment

Learning outcomes

Student knows:

the basic theory about the data fusion concept,

the rules of data fusion models, architectures and levels division,

the procedure of the data registration process,

the commonly used quality factors,

examples of most commonly used algorithms.

Student can design, adopt, proceed and assess the data fusion algorithm for exemplary

cases.

40

Required readings

1. D. L. Hall, Sonya A. H. McMullen: Mathematical Techniques in Multisensor Data Fusion,

Artech House Publishers, 2004

2. M. E. Liggins, D. L. Hall, James Llians: Handbook of Multisensor Data Fusion, CRC Press

LLC, 2nd ed., 2009

Supplementary

readings

1. L. A. Klein: Sensor and Data Fusion. A tool for Information assessment and Decision

Making., SPIE Press, 3rd ed., 2010

2. X. E. Gros: Application of NDT Data Fusion, Kluwer Academic Publishers, 2001

3. H.B. Mitchell, Multi-Sensor Data Fusion: An Introduction, Springer, 2007, ISBN

3540715592, 9783540715597


Course title INTRODUCTION TO SOUND RECORDING TECHNOLOGY

Field of study Electronics and Telecommunications


Teaching method lectures, workshop, laboratory, project





Course code


Type of course optional Level of course Bachelor, master



Objectives of the

course

To provide knowledge on selected topics on sound engineering, recording technology and

electroacoustical measurements.

Entry requirements/

prerequisites Basic knowledge in Physics

Course contents

Lectures: Objectives of sound engineering and recording technology. Basics of musical

sound descriptions. Sound sources properties. Two- and multichannel reproduction

systems. Electroacoustical transducers and electroacoustical systems. Microphone

technique. Analog and digital recording systems. DAW. Digidal audio signal processing.

Production of speech and music recordings. On location recording techniques. Mastering.

Labs: measurements of sound intensity, parameters of microphones and loudspeakers,

stereo recordings using AB, XY, MS and ORTF methods, mixing desk applications,

reverberation time measurement. Production of recordings sessions in studio and on

location, non-linear sound editing, mastering


Learning outcomes

Students will be able to explain the basic techniques of recording, processing and play back

audio signals. Also gain the skills in electroacoustic and sound recording system use, design

and measurements.

41

Required readings 1. Howard D. H.: Acoustics and psychoacoustics. Focal press, 2001.

2. Everest F. A.: Master handbook of acoustics. McGraw-Hill, 2001.

Supplementary

readings

1. Blauert J.: Spatial Hearing - Revised Edition: The Psychophysics of Human Sound

Localization. MIT Press, 1999.


Course title M.Sc. Thesis

Teaching method Individual work with the thesis supervisor


the course

Depends on the subject of the

thesis


responsible for the course

Course code




Hours per week Hours per semester 15 hours

Objectives of the

course

This course is intended to help students with their M.Sc. thesis. The work is either a project

or a research. It can result in e.g. creating a computer program, laboratory work station, a

device-model or presenting results of research carried out using professional devices or

programs.

Entry requirements

- Knowledge of basic issues related to the subject of the thesis

- Ability to formulate technical texts and prepare drawings and diagrams presenting

gained results

Course contents

Doing a M.Sc. thesis is in fact realization of a complex engineering task containing scientific

elements, that starts with formulating a problem and making assumptions, analyzing

current state of the art and defining the scientifically justifiable method of realizing the aim

of the work. At the end of the task, the student formulates conclusions and prepares written

description of performing the task, its results and analysis.

Assessment methods Continuous assessment and instructions given by the supervisor

Learning outcomes

Knowledge of modern solutions and the scientific achievements related to the subject of

the thesis, ability to write detailed technical reports and prepare related multimedia

presentations, ability to find the necessary information in the scientific literature and

technical documentation

Recommended

readings Depends on the subject of the thesis

Additional information Please contact the faculty Erasmus coordinator to discuss the details of the course.



42

Course title MACHINE LEARNING

Field of study ICT



the course Adam Krzyzak



Course code





Objectives of the

course

This course is intended to present a unified approach to machine learning techniques and

algorithms and their applications in practical problems

Entry requirements/

prerequisites


basic knowledge about programming

basic knowledge of linear algebra, probability and statistics

Course contents

Classification. Generative vs. discriminative learning. Naive Bayes. Gaussian discriminant

analysis. Linear models: linear and polynomial regression, overfitting, model selection, L2

and L1 regularization, sparse models, logistic regression. Non-linear models: decision trees,

instance-based learning, boosting, neural networks. Support vector machines and kernels.

Computational learning theory. Unsupervised learning: clustering, K-means, mixture models,

density estimation, expectation maximization. Autoencoder, PCA, eigenmaps and other

dimensionality reduction methods. Structured models: graphical models, Bayes nets.

Learning in dynamical systems: Hidden Markov Models and other types of

temporal/sequence models. Approximate inference. Gibbs sampling. Deep belief learning.


Learning outcomes Knowledge of basic machine learning algorithms. Ability to implement some machine

learning algorithms in chosen environment (e.g. Matlab).

Required readings 1. Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.

Supplementary

readings

1. Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical

Learning, Second Edition, Springer, 2009.

2. Garreth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, An Introduction to

Statistical Learning, Springer, 2013.

3. Ethem Alpaydin, Introduction to Machine Learning, Second Edition, MIT Press, 2009.

4. Tom Mitchell, Machine Learning, McGraw-Hill, 1997


43

Course title MANAGING MODEL-BASED DEVELOPMENT

Field of study Control Engineering, ICT

Teaching method Lectures, simple examples; Lab – software tools learning with examples; Project – computer

modeling


the course Krzysztof Pietrusewicz



the course

[email protected]

Course code


Type of course Obligatory Level of course Bachelor/Master


Hours per week 1 Lecture, 1 Lab, 1 Project Hours per semester 15 Lecture, 15 Lab, 15 Project

Objectives of the

course

This course is intended to present basics of managing model-based design and

development with the use of modern software tools. Additional goal is to present possible

workflows of implementation of model-based design procedures in industry.

Entry requirements/

prerequisites

Mechatronics, Control theory, Computer science, Requirements management in research

projects on complex systems, Modeling of complex systems with the use of SysML

Course contents

1. Phases of model-based design, understanding purposes of V-model 2. Graphical

specifications 3. Code generation possibilities 4. Simulation possibilities 5. Hardware in the

loop: when and how? Science or industry? 6. Virtual verification and validation 7. Workflows

for effective implementation of model-based design

Assessment methods Lectures – project public presentation during seminar, Lab – validation on preparation level,

Project – continuous assessment

Learning outcomes

After this course student is able to:

1. understand the need for managing system models

2. have knowledge about modern software and hardware tools used for industry oriented

model-based design

3. see the need of create clear connections between production code of control system with

its graphical specifications

4. conduct virtual verification and validation procedures within mechatronic projects

5. understand obstacles on the road of effective implementation of model-based design in

industry

Required readings

1. Holt J., Perry S.A., Brownsword M., Model-based requirements engineering, 2012, ISBN

978-1-84919-487-7

2. ISO/IEC/IEEE 29148:2011, Systems and software engineering - Life cycle processes -

Requirements engineering. 2011

3. Friedenthal S., Moore A., Steiner R., A practical guide to SysML. The systems modeling

language, 2015, ISBN 978-0-12-800202-5

4. Delligatti L., SysML distilled, A Brief Guide to the Systems Modeling Language, 2014, ISBN

978-0-321-92786-6

5. Aarenstrup R., Managing model-based design, 2015, ISBN-13: 978-1512036138

44

Supplementary

readings

1. The Official OMG SysML website, http://www.omgsysml.org/

2. Papyrus UML for Eclipse website, https://eclipse.org/papyrus/

3. Visual Paradigm website, http://www.visual-paradigm.com/

4. Sparx Enterprise Architect website, http://www.sparxsystems.com.au/

5. Mathworks official website, http://www.mathworks.com/


Course title MEDICAL IMAGING SYSTEMS

Field of study Image Processing

Teaching method lectures, labs


the course Piotr Okoniewski



Course code


Type of course compulsory Level of course master



Objectives of the

course

To provide up to date knowledge on various modalities of biomedical imaging technologies

and algorithms to develop practical skills useful in this area.

Entry requirements/

prerequisites Mathematics, Informatics, Signal processing, Image processing, Biomedical Engineering

Course contents

Lectures: Medical imaging systems – physical principles of image formation and equipment

in Thermography (TG), Ultrasonography (USG), Nuclear Medicine (Gamma-camera, SPECT,

PET), Digital Radiography (DR), Computed Tomography (CT), Magnetic Resonance Imaging

(MRI). Special techniques, e.g. ultra-fast data acquisition systems in MRI (EPI), Functional

and Interventional MRI. Principles of image reconstruction (2-D, 3-D). Image processing,

analysis and measurement; software tools. Image fusion. Image transmission and archiving

– PACS, standard DICOM 3. DICOM validation tools

Labs: Image browsing & analysis tools: systems OSIRIS/PAPYRUS and PC-Image. DICOM

validation tools. MATLAB and LabView systems in image processing.

Assessment methods Lectures: grade, accomplishment of lab tasks

Learning outcomes

The student has increased knowledge on methods and techniques used in medical

diagnostic imaging, systems and archiving/communication standards as well as on research

methodology used in this field. He has practical skills useful in this area regarding

biomedical imaging systems testing, development, and exploitation

http://www.omgsysml.org/

https://eclipse.org/papyrus/

http://www.visual-paradigm.com/

http://www.sparxsystems.com.au/

http://www.mathworks.com/

45

Required readings

1. Bronzino J. D. (ed.): “Biomedical Engineering Handbook”. CRC Press, IEEE Press, 1995

2. Robb R. A.: “Three Dimensional Biomedical Imaging: Principles and Practice”. Wiley-Liss,

N.Y., 1998

3. Shellock F. G., Kanal E.: “Magnetic Resonance. Bioeffects, Safety and Patient

Management”. Raven Press, N.Y., 1994

Supplementary

readings

1. Huang H. K.: “PACS in Biomedical Imaging”. VCH Publ. Inc., N.Y., 1996

2. IT-EDUCTRA. FUNDESCO, Commission of the EC, 1998


Course title MODELING OF COMPLEX SYSTEMS WITH THE USE OF SYSML



modeling





course

[email protected]

Course code




Hours per week 1 Lecture, 1 Lab, 1

Project Hours per semester 15 Lecture, 15 Lab, 15 Project

Objectives of the

course

This course is intended to present basics of complex system modeling, software tools and

methods for effective representation of complex systems with the use of graphical

specifications, that can be used for control software code generation purposes.

Entry requirements/

prerequisites

Mechatronics, Control theory, Computer science, Requirements management in research

projects on complex systems

Course contents

1. Modeling complex systems – where is a need for that? 2. Breakdown of complex systems

into simple functional units 3. How to combine requirements with implementation

(structure and behavior of system components) and testing (unit, interface, integration)

4. SysML graph types 5. Example of complex system modeling from automotive industry

6. Example of complex system modeling from machine tool industry



Learning outcomes


1. understand the need for modeling systems

2. create selected SysML graphs for complex systems modeling

3. create interactions between different SysML models and combine them within integrated

system model

4. create documentation for the modelled/designed system

46

Required readings


978-1-84919-487-7



3. Friedenthal S., Moore A., Steiner R., A practical guide to SysML. The systems modeling

language, 2015, ISBN 978-0-12-800202-5

4. Delligatti L., SysML distilled, A Brief Guide to the Systems Modeling Language, 2014, ISBN

978-0-321-92786-6

Supplementary

readings





5. Mathworks official website, http://www.mathworks.com/


Course title MODERN ELECTRICAL MACHINES


Teaching method Lecture, Project


the course Ryszard Pałka



Course code


Type of course Obligatory or optional Level of course master


Hours per week 2L / 1P Hours per semester 30L, 15P

Objectives of the

course

The course gives the fundamental and expert knowledge about construction, development,

numerical evaluation and optimization of modern electrical machines.

Entry requirements/

prerequisites

Basics of electrical engineering, basics of electrical machines, electromagnetic field theory,

numerical methods.

Course contents

The course gives the knowledge about construction of modern electrical machines:

Permanent magnet excited synchronous machines,

Transverse flux machines, axial flux machines,

Switched reluctance machines,

Different electrical machines for hybrid and pure electric vehicles.

Assessment methods Written exam, project work

Learning outcomes





http://www.mathworks.com/

47

Required readings

1. Gieras J. F., Wing M.: Permanent magnet motor technology. Wiley&Sons 2008

2. Austin Hughes; Electric Motors and Drives. Elsevier Ltd. 2006

3. Chiasson J.: Modeling and high-performance control of electric machines. Wiley&Sons

2005

4. Larminie J., Lowry J.: Electric Vehicle Technology Explained. Wiley&Sons 2003

Supplementary

readings

1. Gieras J. F., et al.: Noise of Polyphase Electric Motors. CRC Press 2006

2. Pyrhoenen J., et al.: Design of Rotating Electrical Machines, Wiley & Sons, 2008


Course title MULTISTRUCTURED OPTICAL FIBRES APPLICATIONS

Field of study

Electronics and Telecommunications ,

Automatic Control and Robotics,

Electrical Engineering ,

Teleinformatics



the course

Prof. Ewa Weinert-Raczka

Dr Grzegorz Zeglinski



course

[email protected]

Course code

(if applicable)

ECTS points 2



Hours per week 1h-lecture, 1h-project Hours per semester 15h—lecture

15h-project

Objectives of the

course

The first objective of this course is to give basic

concepts relating to special optical fiber

Entry requirements/

prerequisites

Course contents

1. Introduction to optical fiber theory.

2. Fabrication of fibres

3. Modes of Optical Fibers. Single Mode and Multimode Fibres.

4. Chromatic Dispersion.

5. Polarization Mode Dispersion.

6. Holey and Photonic Crystal Fibres. Photonic Bandgap Guidance.

7. SuperContinnuum Generation.

8. Optical Fibres for sensors

9. Fiber Bragg Gratings

10. Multicore Fibres

11. Polymer Optical Fibres

12. Optical Fibers Interferomers

13. Modelling and Design of Microstructured Fibres

14. Application of Special Optical Fibres

48

Assessment methods project work

Learning outcomes

At successful completion of this course the students will be familiar with special optical

fibers - propagation, modelling and design. The

course will also provide the basic knowledge of

methods of propagation modeling in Microstructured Opticial Fibres and applications of

special optical fibres

Required readings

1] Argyros A.: Microstructures in Polymer Fibres for Optical Fibres, THz Waveguides, and

Fibre-Based Metamaterials, Institute of Photonics and Optical Science, School of Physics,

The University of Sydney, Sydney, NSW 2006, Australia

[2] Ziemann O., Krauser J., Zamzow P.E., Daum W.: POF Handbook, Optical Short Range

Transmission Systems. Springer-Verlag, 2008.

Supplementary

readings


Course title NETWORK SYSTEMS ADMINISTRATION

Field of study ICT



the course Piotr Lech



Course code


Type of course obligatory Level of course bachelor


Hours per week 1 Lecture / 2 Lab. Hours per semester 15 Lecture/

30 Laboratory

Objectives of the

course

The course introduces students to the fundamentals of network management, primarily for

TCP/IP networks. Students are introduced to networking protocols, hardware, architecture,

media, and software and experience hands-on management of typical network

components.

Entry requirements/

prerequisites Prerequisites and additional requirements not specified

Course contents

Determine the network design most appropriate for a given site. Installation and

configuration of network services. Differentiate among network standards, protocols, and

access methods. Master local area network concepts and terminology. Network planning,

network equipment (hub, switch, router). Protocols TCP/IP, IP nets, IP subnets, VLAN .

Protocol analysis. Network administration (SNMP, RMON)

Assessment methods Written exam (test), continuous assessment (laboratory)

49

Learning outcomes

Working knowledge of networking terms and concepts pertaining to system administration,

terms that characterize the attributes of networks and aspects of network operation. Ability

to observation of system behavior. Ability actions taken to accomplish sysadmin related to

administration tasks.

Required readings

1. Tony Bautts, Terry Dawson, Gregor N. Purdy Linux Network Administrator's Guide, 3rd

Edition O'Reilly Media 2005 ISBN: 978-0-59600-548-1 AEleen Frisch Essential System

Administration, 3rd Edition O'Reilly Media 2002 ISBN:978-0-59600-343-2 Sander van

Vugt Pro Ubuntu Server Administration Apress 2008 ISBN: 978-1-4302- 1622-3

Supplementary

readings Selected RFC documents.


Course title NETWORK TRAFFIC

Field of study ICT

Teaching method Lecture + laboratory





the course

[email protected]

Course code




Hours per week 1 lect. / 2 lab. Hours per semester 15 lect. / 30 lab.

Objectives of the course This course is intended to present selected issues of ICT network traffic and performance

evaluation.

Entry requirements/

prerequisites Fundamentals of computer networks.

Course contents

Configuration and performance evaluation for different network setups (bandwidth, buffer

size, transport layer protocols). Capturing, filtering and inspecting of L2 and L3 layers. Delay

and loss analysis. Network traffic generation model. Synthesis of traffic flows based on

stochastic processes. Collecting data using SNMP. Traffic shaping and control using

classless (SFQ, GRED, TBF) and classful (HTB, CBQ, PRIO) queueing disciplines. Basic queues

and their impact on network traffic. Configuration of multicast and real-time applications

(IGMP, RSVP, RTP).

Assessment methods Written exam (test), assessment and reports (lab.)

50

Learning outcomes Knowledge of network traffic issues and performance evaluation. Ability to configure and

control network traffic in various applications (best effort, real-time).

Required readings 1. Armitage G.: Quality of Service in IP Networks: Foundations for a Multi-service Internet,

2000.

Supplementary

readings

1. Welzl M.: Network Congestion Control: Managing Internet Traffic, 2005.

2. Ash G. R.: Traffic Engineering and QoS Optimization of Integrated Voice and Data

Networks, 2006.


Course title NON-DESTRUCTIVE TESTING (NDT) USING RADIOGRAPHIC (X-RAY) AND

TERAHERTZ METHOD

Field of study Electrical engineering, Mechanical engineering

Teaching method Lecture and laboratory experiments


the course Tomasz Chady



Course code


Type of course Obligatory

Level of course Bachelor, Master



Objectives of the

course

To give basic knowledge of techniques for non-destructive testing (NDT),

To teach how to apply Xray and THz method in practical applications,

To introduce modern systems and techniques for NDT

Entry requirements/

prerequisites Academic course of mathematics and physics (required)

Course contents

Non-destructive testing - the introduction, the basic idea, the historical background

Review of different methods of non-destructive testing

Radiation Sources

Computer radiography using imaging plates

Digital radiography

Evaluation of low conductivity materials using electromagnetic waves of high frequency

(THz – terahertz TDS imaging)

Simulators of NDT systems,

The algorithms of digital signal processing in NDT

Industrial tomography

Special Radiographic Techniques



51

Assessment methods Continuous assessment (Lect.) + Continuous assessment (Lab)

Learning outcomes


identify, formulate, and solve engineering problems in the field of NDT,

explain the principles of the major NDT methods,

identify advantages and limitations of nondestructive testing methods and to select the

appropriate techniques for inspections in specific application,

use selected software for numerical modelling of NDT systems,

use selected hardware for practical NDT (i.e. THz TDS or digital detectors and IP scanner

for X-ray testing).

Required readings 1. Hellier C. J., Handbook of Nondestructive Evaluation, McGrown-Hill, 2003

2. Sakai K., Terahertz Optoelectronics, Springer-Verlag Berlin Heidelberg 2005

Supplementary

readings

1. Nondestructive Testing Handbook, Third Edition: Volume 4, Radiographic Testing (RT),

ASNT, 2005.


Course title NONLINEAR CONTROL


Teaching method Lectures covering basic modelling of nonlinear systems, dynamics, control methods.

Laboratory course covering various applications and control design.





Course code



Semester Winter / summer Language of instruction english

Hours per week 1h lecture, 2h laboratory Hours per semester 15h lecture,

30h laboratory

Objectives of the

course The Student will learn to design and apply nonlinear control methods.

Entry requirements/

prerequisites Linear control, Dynamical systems, Mathematics, Physics

Course contents

This course covers modelling of nonlinear systems using Newton-Euler and Euler-Lagrange

methods, stability analysis using Lyapunov functions, passive systems, phase-plane

portraits, feedback linearisation, partial feedback linearisation for underactuated systems

and control analysis. The laboratory course covers modelling and control of basic nonlinear

systems, using both simulation and laboratory equipment (inverted pendulum on a cart,

motor positioning, simple robotic manipulator).

52

Assessment methods Written exam (on last lecture), Continuous assessment during laboratory course

Learning outcomes Ability to model, analyse and control a nonlinear system.

Required readings 1. Slotine, Jean-Jacques E., and Weiping Li. Applied nonlinear control. Prentice-hall, 1991.

Supplementary

readings

1. Khalil, Hassan K. Nonlinear systems. Prentice Hall, 1996

2. Featherstone, Roy. Rigid body dynamics algorithms. Springer, 2008.

3. Isidori, Alberto. Nonlinear control systems. Springer, 1995.


Course title OBJECT-ORIENTED PROGRAMMING IN C#


Technology Engineering






Course code






Lectures - 30

Laboratory – 30

Objectives of the

course

This course is intended to present object-oriented programming techniques in C#

language.

Entry requirements/

prerequisites Mathematics

Course contents

10. Application structure in C#

11. Data Types

12. Loops

13. Static Methods

14. Exceptions

15. Files and Streams

16. Arrays

17. Structures

18. Classes

19. Constructor

20. Inheritance

21. Abstract Classes

22. Polymorphism


53

23. Collections

24. Windows Forms


Learning outcomes Students will get the knowledge about modern object-oriented language.

Required readings

1. A. Hejlsberg, M. Torgersen, S. Wiltamuth, P. Gold: The C# Programming Language,

Addison-Wesley, 2011

2. D. Clark: Beginning C# Object-Oriented Programming, APress, 2011

3. M. McMillan: Data Structures and Algorithms using C#, Cambridge University Press,

2007

Supplementary

readings


Course title OPTIMIZATION THEORY








Course code


Type of course Obligatory Level of course Master




Lectures - 30

Laboratory – 30

Objectives of the

course

This course is intended to present a unified approach to various optimization methods

(advanced undergraduate level).

Entry requirements/

prerequisites Numerical Methods, Mathematics, Physics

Course contents

1. One-Dimensional Search Methods (Golden Section Search, Fibonacci Search, Newton's

Method, Secant Method)

2. Gradient Methods

3. Genetic Algorithms

4. Simplex Methods, Non-Simplex Methods

5. Single Objective Optimization and Multi Objective Optimization Problems

6. Discrete Ill-Posed Problems

7. Direct Regularization Methods

8. Iterative Regularization Methods


54

9. Methods for Choosing the Regularization Parameter

10. A Discrete L-Curve for the Regularization of Ill-Posed Inverse Problems

11. Single Objective Optimization of an Exciter for Magnetic Induction Tomography

12. Multi Objective Optimization of an Exciter for Magnetic Induction Tomography

13. Magnetic Field Synthesis on a Solenoid's Axis (Solving Ax = b using Least-Squares

Analysis, Recursive Least-Squares Algorithm, Solution to Ax = b Minimizing ||x||)

14. Topology Optimization of a Magnetic Field in a Three-dimensional Finite Region


Learning outcomes Students will get the knowledge about various optimization methods. They will be able to

use an appropriate method to the given practical problem.

Required readings

1. Edwin K.P. Chong, Stanislaw H. Żak: An Introduction to Optimization, Second Edition,

Wiley & Sons, Inc, 2001, New York, USA

2. R. Fletcher: Practical Methods of Optimization, second Edition, Wiley, 2000

Supplementary

readings

1. Per Christian Hansen: Regularization Tools, Technical University of Denmark, Lyngby,

2008


Course title PATTERN RECOGNITION AND CLASSIFICATION

Field of study ICT



the course Adam Krzyzak



Course code





Objectives of the

course

This course is intended to present a unified approach to pattern recognition and

classification techniques and their applications in real life problems

Entry requirements/

prerequisites


basic knowledge about programming

basic knowledge of linear algebra, probability and statistics

55

Course contents

Introduction to the subject of pattern recognition. Bayesian decision theory, discriminant

functions for normal class distributions, parameter estimation and supervised learning,

nonparametric techniques (nearest neighbor rules, Parzen kernel rules, tree classifiers),

Adaboost, Breiman random forest, linear discriminant functions, Fisher linear discriminant

and learning including perceptron learning, LMS algorithms and support vector machines,

unsupervised learning and clustering, neural networks including multilayer perceptrons and

radial basis networks, and elements of machine learning. Feature selection and

dimensionality reduction including PCA, SOM and Laplacian maps. Applications of pattern

recognition in biometrics including handwriting recognition, face recognition and

fingerprint recognition.


Learning outcomes Knowledge of basic pattern recognition algorithms. Ability to implement some pattern

recognition algorithms in chosen environment (e.g. Matlab).

Required readings 1. R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, Wiley, Second Edition,

2001.

Supplementary

readings

1. Sergios Theodoridis and Konstantinos Koutroumbas, Pattern Recognition, Fourth

Edition, Academic Press, 2008.

2. Brian Ripley, Pattern Recognition and Neural Networks, Cambridge University Press,

2008.

3. Simon Haykin, Neural Networks and Learning Machines, Third Edition, Prentice Hall,

2008.

4. Nello Cristianini and John Shawe-Taylor, An Introduction to Support Vector Machines

and other Kernel-Based Learning Methods, Cambridge University Press, 2000.


Course title POWER ELECTRONICS FOR RENEWABLE ENERGY SOURCES

Field of study Electrical engineering, automatic control systems, industrial electronics, energy,

mechatronics

Teaching method lecture / project


the course

Marcin Hołub



Course code




Hours per week 1Lecture / 2Project Hours per semester 15 Lecture

30 Project

Objectives of the

course

Student will be able to:

- recognize and distinguish basic types of renewable electrical energy sources.

- distinguish basic characteristics of different sources.

- distinguish basic types of photovoltaic modules and their main properties, will be

able to draw basic waveforms.

56

- distinguish basic types of solar converters.

- give basic properties and characteristics for main types of switched mode power

supplies.

- perform basic calculations for main circuit components and adjust component

type and kind.

- use CAD software for basic simulations and basic types of projects.

- perform basic project for a small scale power converter.

- analyze basic structures of power converters and draw main schematics for system

components.

Entry requirements/

prerequisites Electronics, basics of electrical engineering

Course contents

Power electronics for renewable energy sources: past and present of energy production and

consumption, perspectives, connections with other technical branches. Basic electrical and

eletromechanical properties of photovoltaic panels and modules. Fuel cells – construction,

properties, dynamic response. Wind energy – basics, Betz’s limit, basic constructions. Power

electronic converters for energy conversion. Switched mode power supplies, MPP tracking.

Single and three phase inverters. Converter groups for photovoltaic systems, wind energy

converters. Grid connection. Summary.

Assessment methods Written tests

Project work assessment

Learning outcomes

Ability to distinguish properties and characteristics of various renewable energy sources.

Ability to define proper power electronic converter chain. Ability to construct small – scale

converters for PV modules. Ability to construct simple simulation models. Ability to prepare,

set-up and conduct measurements and draw conclusions.

Required readings

1. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-1McGrawHill

2009

2. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill 1999


Supplementary

readings


Course title POWER SYSTEM ENGINEERING

Field of study Power Engineering

Teaching method

The lectures and laboratories are going in parallel. During lectures, the teacher, using classic

whiteboard and presentation, will teach about power electric system in Poland. During

laboratories students will have possibility to verify their knowledge about power electric

system and simulate its behavior using real models of network in laboratory.


the course Dr inż. Michał Balcerak



Course code



57



Objectives of the

course

Student has knowledge on power electric network – how it works, how to generate power

for electric consumer, what the properties of electric load are and witch of them are

important for the power system.

Entry requirements

/prerequisites

Student should know math (trigonometric and complex numbers) and basics of Electric

Engineering.

Course contents

Electric loads: power factor, current distortion factor,

Electric grid properties: impedance of electric grid, voltage drop, voltage losses and power

loses on the wires,

Correct methods of current, voltage and power measurement in three phase grid,

Generation and distribution of power

Assessment methods Laboratories measurement report assessment and final test on the end of the course

Lectures final written exam

Learning outcomes

Students will know:

- types of power plant, methods to produce energy in conventional and unconventional

power plant

- typical and distributed types of electric power grid

- method of reactive power compensation (Q), influence of Q to a loos of voltage and

power in power electric grid

- how to stabilize frequency and voltage in grid

- methods to decrease levels of higher harmonics of voltage and current in power electric

systems

- about power electronics devices in power electric grid: HVDC grids, PFC, distortion

reduction

Required readings

Supplementary

readings

1. D.P. Kothari, I.J. Nagrath, Power System Engineering, Tata McGraw-Hill Education, 2008

2. S. Sivabagaraju, S. Satyanarayana, Electric Power Transmission and Distribution, Pearson

Education 2009

3. D.F. Warne, Newnes Electrical Power Engineer's Handbook, 2005, ELSEVIER

4. Alexander S. Graffeo, The Electrical Engineer's Guide to passing the Power PE Exam,

2012

Additional information Maximum 12 persons in one laboratory group.

Course title POWER SYSTEM PROTECTION


Teaching method Lecture/laboratory





58

Course code


Type of course Obligatory/elective Level of course Bachelor



Objectives of the

course

Knowledge about principles of power system protection,

Skills of selection of protection for basic components of power system.

Entry requirements/

prerequisites Mathematics, physics, basis electrical engineering.

Course contents

Interferences in power system, overload protection, overcurrent protection, overvoltage

protection, undervoltage protection, differential protection, directional protection, distance

protection, protection of transformers, protection of lines, protection of busbars, protection

of generators, protection of electrical motors, investigation of overcurrent protection,

investigation of overvoltage protection, investigation of undervoltage protection,

investigation of distance protection, investigation if differential protection.

Assessment methods Continuous assessment in laboratory, final test on the end of lectures

Learning outcomes

Knowledge:

Student has knowledge for understanding principles of protection for basic components of

power system,

Skills:

Student is able to choice the protections for basic components of power system,

Required readings

Supplementary

readings





2007,






Course title PROBLEM-SOLVING WORKSHOP

Field of study

Teaching method

lab and project work, seminars

59





Course code




Hours per week

4 (2Lab, 1P, 1S-average) Hours per semester 60 (30Lab, 15P, 15S)

Objectives of the

course

To provide knowledge on research and design methods and to develop various skills useful

in solving bioengineering problems.

Entry requirements/

prerequisites

Physics, Informatics, Signal processing, Image processing, Telecommunications, Computer

Systems, Biomedical Engineering, fundamentals of semiconductor electronics.

Course contents

Research work (individual or in 2-3 students teams) is run on topics corresponding to the

area of all courses. The topics are offered by the teachers and chosen by the students at the

beginning of the semester, after consultations; the topics may be also proposed by the

students. Projects are run using all facilities of the Department of Systems, Signals and

Electronics Engineering and co-operating Departments (including rooms, laboratory

equipment, computers & software, Internet access, library, copying facilities etc.).

Consultations with supervisors – the teachers involved in all projects - are performed

regularly during the semester, with presentation of the progress of research work in the mid

of the semester, in a form of a seminar open for all students and teachers (6h). Final

assessment of a particular project is made after evaluation of the written report by the

supervisor and reviewer, on the basis of oral presentation or a poster during the second,

final seminar (9h) .

Assessment methods Continuous assessment of lab and project work, evaluation of the written report and of

oral/poster presentation of the project results during the final seminar.

Learning outcomes

The student has knowledge on research and design methodology, and on performing

project work. He has practical skills useful in solving interdisciplinary problems in the field of

biomedical engineering.

Required readings Recommended materials for all courses of the SPE-1 program in BME.

Supplementary

readings Recommended materials for all courses of the SPE-1 program in BME .


Course title PROGRAMMABLE AUTOMATION SYSTEM BASED ON PLC AND HMI

Field of study

Automatic Control and Robotics, Electrical Engineering, Mechanical Engineering,

Management and Production Engineering , Information and Communications Technology,

Electronics and Telecommunications, Architecture and Urban Planning - Civil Engineering

60

Teaching method Lecture, project, laboratory


the course Krzysztof Jaroszewski



Course code


Type of course Compulsory/optional Level of course bachelor


Hours per week 1 (L) 1 (P) 1 (Lab) Hours per semester 1 (L) 1 (P) 1 (Lab)

Objectives of the

course

To form skills of programming automation system consists of: Programming Logical

Controllers (PLC’s) - in the control level and Human Machine Interfaces (HMI’s) – in maintain

level. Moreover, subject with diagnostic and fault tolerant control algorithms will be bring

closer. During practical parts of the course SIMATIC by SIEMENS devices will be used: PLC:

S7-1200, HMI: KTP600.

Entry requirements/

prerequisites Elementary knowledge in the subject of mathematical logic

Course contents

Automatic systems – basic knowledge. Programmable devices in automaton of industrial

processes: PLC, HMI, SCADA, DCS and their tasks. PLC’s programming languages and

cycled operating. Diagnostic of industrial processes methods.

Assessment methods Grade

Project work

Learning outcomes Ability to design automation system including elementary diagnostics and built project on

PLC and HMI.

Required readings

Curse materials

Manuals by SIEMENS

Automating with SIMATIC S7-1200: Configuring, Programming and Testing with STEP 7

Basic, Hans Berger, ISBN: 978-3-89578-901-4

Supplementary

readings

1. Programmable Logic Controllers: An Emphasis on Design and Application, Kelvin T.

Erickson, ISBN-13: 978-0976625926


Course title PROGRAMMABLE LOGIC DEVICES

Field of study




Teaching method lectures, laboratory, project





61

Course code


Type of course compulsory Level of course Bachelor, master

Semester Winter or Summer Language of instruction English

Hours per week 1L/1Lab/1Project Hours per semester 15L/ 15Lab/ 15Project

Objectives of the

course

To provide knowledge on programmable logic devices and its use in modern digital system

design

Entry requirements/

prerequisites Basic knowledge on digital circuits and informatics

Course contents

Lectures: Categorization of programmable logic devices. Design systems for SPLD and

CPLD. Configuration memory. ABEL. Properties and configuration of logic blocks (LUT, FF)

and I/O in FPGA. Specialized blocks – RAM, multipliers. Distribution of clock signals (PLL,

DLL). Metastability. Abstraction levels in digital systems description. Elements of VHDL in

synthesis of digital systms. Designing paths. Design environments for FPGA design. JTAG.

Systems on Chip. Structured ASIC.

Labs: PLD synthesis using VHDL and laboratory boards.

Project: Design and testing of various digital systems designed using FPGA laboratory

boards.

Assessment methods Written exam, accomplishment of practical labs and projects

Learning outcomes

Student will be able to describe the building blocks in modern CPLD and FPGA integrated

circuits. Student will be able to design and test simple digital appliances using

programmable IC's and hardware description language.

Recommended

readings

1. Skahill K.: VHDL. Design of programmable logic devices. Prentice Hall 2001

2. Sunggu Lee, Design of computers and other complex digital devices, Prentice Hall 2000

3. Perry D. L.: VHDL. McGrawHill, 1997.

Supplementary

readings

1. Oldfield J. V., Dorf R. C.: FPGAs. Reconfigurable Logic for Rapid Prototyping and

Implementation of Digital Systems. John Wiley&Sons, Inc., N.Y., 1995.

2. Xilinx data sheets and programmer literature at www.xilinx.com.


Course title RENEWABLE ENERGY SOURCES

Field of study Power Engineering, Renewable Energy Sources

Teaching method The teacher, using PowerPoint presentation, movies and classic whiteboard, will teach about

small and large renewable energy sources for power electric grid.


the course Dr inż. Michał Balcerak



http://www.analog.com/

62

Course code



Semester winter/summer Language of instruction English

Hours per week 2L Hours per semester 30 L

Objectives of the

course

Student has knowledge on method of power generation – how a power plants works and

what’s the methods of energy storage.

Entry requirements/

prerequisites

Student should know math (trigonometric and complex numbers) and basics of Electric

Engineering and Electric Motors.

Course contents

Description of followed power plants: conventional, photovoltaic, wind, water, solar, nuclear,

fusion, geothermic, biomass, etc.

Description of energy storage methods for domestic and large-scale grids.

Assessment methods Final test on the end of the course

Learning outcomes

Students will know:

- types of power plant, methods to produce energy in conventional and unconventional

power plant

- methods of storage the energy for small- and large-scale electric grid.

Required readings

Supplementary

readings


Course title REQUIREMENTS MANAGEMENT IN RESEARCH PROJECTS ON COMPLEX

SYSTEMS



modeling





the course

[email protected]

Course code



Semester Winter or summer Language of

instruction English

Hours per week 1 Lecture, 1 Lab, 1 Project Hours per semester 15 Lecture, 15 Lab, 15 Project

63

Objectives of the

course

This course is intended to present basics of requirements management, software tools and

methods for effective tracing and change management of initial requirements within

interdisciplinary research projects of complex systems.

Entry requirements/

prerequisites Mechatronics, Control theory, Computer science

Course contents

1. Definition of project requirements 2. gathering requirements from stakeholders within

interdisciplinary project (bridge between Universities and industries, understanding goals

issues) 3. Graphical modeling of project requirements 4. Requirements traceability and

change issues 5. Workflows models for interdisciplinary research teams, including

approaches for teams with different experience level



Learning outcomes


1. identify and model requirements, including prioritization of requirements stated

2. understand influence of modeling requirements for team efficiency as compared with

classic realization of projects

3. understand the need of requirements traceability during development of control software

for complex mechatronic systems

Required readings


978-1-84919-487-7



Supplementary

readings






Course title ROBOT DYNAMICS AND CONTROL

Field of study Automatic control and robotics



the course Rafał Osypiuk



Course code


Type of course Optional Level of course Master

Semester Summer Language of instruction English

Hours per week 1 (L) 1 (Lab) Hours per semester 15 (L) 15 (Lab)





64

Objectives of the

course

The student will gain competences related to evaluation of complex process, including their

non-linearity or time-varying nature and methods of elimination thereof, both during the

robotic-arm design and during control system synthesis. Additionally, the student will gain

the ability to choose the appropriate control structure and to verify its property through

low-level use of the simulation environment.

Entry requirements/

prerequisites Mathematics, Mechanics, Introduction to robotics, Programming languages

Course contents

The course includes selected topics of dynamics modelling and position control methods

related to industrial robots. In particular, the course discusses mathematical description of a

robotic-arm in the presence of forces/torques and methods of its used in implementations

of advanced control systems. Functional blocks for the Matlab/Simulink environment are

prepared using C programming language, which help to analyse various control strategies,

from a single-loop PID structure to multi-loop solutions with many degrees of freedom.

Assessment methods Grade / project work

Learning outcomes

The ability to modelling of robot dynamics on the basis of mathematical analysis and

correct interpretation of physical phenomena occurring within a kinematic chain. Skills to

implement, simulate and analyse simple and complex control systems, in particular

structures based on forward or inverse plant model.

Required readings

1. Spong M. W., Hutchinson S., and Vidyasagar M., Robot Dynamics and Control,

Introduction to Robotics: Mechanics and Control, 2004, 2nd Edition

2. Craig J. J., Introduction to Robotics: Mechanics and Control , 2004, 3rd Edition

Supplementary

readings

1. Kozłowski K., Modelling and Identification in Robotics, 1998, 1st Edition

2. Siciliano B, Villani L, Robot Force Control, 1999, 1st Edition

3. Siciliano B., Khatib O., Springer Handbook of Robotics, 2008, 1st Edition


Course title SELECTED TOPICS IN NONLINEAR PHOTONICS

Field of study

Electronics and Telecommunications,

Automatic Control and Robotics,

Electrical Engineering ,

Teleinformatics

Teaching method Lecture + laboratory


the course Prof. Ewa Weinert-Raczka



Course code

(if applicable)

ECTS points 2



Hours per week 1h-lecture, 1h-laboratories

Hours per semester

15h—lecture

15h-laboratories

http://www.amazon.com/Bruno-Siciliano/e/B001JOUFOM/ref=dp_byline_cont_book_1

http://www.amazon.com/s/ref=dp_byline_sr_book_2?ie=UTF8&text=Luigi+Villani&search-alias=books&field-author=Luigi+Villani&sort=relevancerank

65

Objectives of the

course

The first objective of this course is to give basic optics and photonics concepts related to

nonlinear optical phenomena

Entry requirements/

prerequisites Basics knowledge in mathematics and physics

Course contents

Nonlinear optical phenomena and their applications: basics of nonlinear photonics,

nonlinear materials, new frequencies generation, phase conjugating mirrors and wavefront

reconstruction, all-optical switching, nonlinear waveguides, temporal and spatial soliton

propagation, reconfigurable photonic circuits, supercontinuum generation.

Assessment methods Lecture, numerical simulations

Learning outcomes At successful completion of this course the students will be familiar with basics of nonlinear

optics and nonlinear photonics applications.

Required readings

1. B. E. A. Saleh, M. C. Teich, Fundamentals of Photonics, Wiley Series in Pure and Applied

Optics, 2007

2. Y. S. Kivschar, G. P. Agrawal, "Optical solitons - From Fibers to Photonic Crystals", Elsevier,

London 2003

Supplementary

readings


Course title SIMULATION AND DESIGN OF POWER ELECTRONIC CONVERTERS


robotics

Teaching method Project / classes





Course code




Hours per week 1 Classes /2Proj Hours per semester 15 Classes /30 Proj.

Objectives of the

course

Student will recognize and distinguish basic switch mode power supply systems. Will learn

how to approach project tasks, deal with projects. Will learn how to simulate (in time

domain, thermal domain and frequency domain) power electronic converters in different

environments. Will learn how to calculate converter components, including magnetics. Will

obtain knowledge on CAD design of power electronic converters. Will get experience in

constructing prototypes, measurement techniques, error elimination methods.

66

Entry requirements/

prerequisites Basics of electrical engineering, basics of power electronics, basics of automatic control

Course contents

1. Project approach and solution theory

2. SMPS converters – non-isolated

3. SMPS converters – isolated topologies

4. Basics of magnetics – inductor

5. Exemplary project calculations

6. Basics of magnetics – HF transformers

7. CAD design rules

8. Prototype construction methods

Assessment methods Project assessment and presentation

Learning outcomes

Ability to calculate and analyze basic SMPS, ability to calculated component values for

different converter topologies. Ability to design and construct simple, power electronic

solutions. Knowledge on prototype testing methods and practical measurements. Ability to

present own work and use technical language.

Required readings

1. M. H. Rashid, Power Electronics Handbook, Elsevier 2007, ISBN-13: 978-0-12-088479-

7

2. Bimal Bose, Power electronics and motor drives, Elsevier 2006, ISBN-13 978-0-12-

088405-6

3. K. Billings, T. Morey, Switching power supply design, ISBN 978-0-07-148272-

1McGrawHill 2009

4. K. Billings, Switchmode power supply handbook, ISBN 0-07-006719-8McGrawHill

1999

Supplementary

readings


Course title SOUND SYSTEM DESIGN

Field of study




Teaching method lectures, seminar, laboratory





Course code


Type of course optional Level of course bachelor, master


67

Hours per week 1L/1S/2Lab Hours per semester 15L/15S/30Lab

Objectives of the

course To provide knowledge and design skills in various sound systems engineering.

Entry requirements/

prerequisites Basic knowledge in Physics and Electronic circuits

Course contents

Lectures: Acoustic wave propagation. The decibel scale. Loudspeakesr and enclosures.

Directivity and angular coverage of loudspeakers. Microphones. Outdoor sound

reinforcement systems. Fundamentals of room acoustics. Behavior of sound systems

indoors. Sound system architectures and its elements. Multichannel hi-fi and cinema sound

systems. Public address and conference systems. Car audio.

Seminar: complementary calculation exercises

Labs: Loudspeaker measurements and design. Room acoustics measurements and

acoustical adaptation design. Microphones measurements and setup. Various sound system

design. Using microphones, loudspeakers, amplifiers, mixing console and sound effects in

sound reinforcement system design. Case studies.


Learning outcomes Knowledge and skills in designing and maintenance of sound systems of various scale and

features.

Required readings

1. Davis D. and C.: Sound System Engineering. Second edition, Howard F. Sams,

Indianapolis, 1987.

2. JBL Professional, Sound System Design Reference Manual,

pdf document available at www.jblpro.com.

Supplementary

readings 1. Eargle J.: Electroacoustical Reference Data. Van Nostrand Reinhold, New York, 1994.


Course title STATISTICAL METHODS IN ICT

Field of study ICT






the course

[email protected]

Course code




68

Hours per week 2 lect. / 2 proj. Hours per semester 30 lect. / 30 proj.

Objectives of the course This course is intended to present statistical methods in ICT for analysis and modeling

purposes.

Entry requirements/

prerequisites Mathematics, basics of computer networks.

Course contents

Statistical data analysis, random variables, distributions, stochastic processes. Traditional

models in Telecommunication Networks: Poisson, Markov Modulated Poisson Process

(MMPP). Estimation of self-similarity in computer networks: R/S analysis, variance-time plot,

Index of Dispertion for Counts (IDC), peridogram and wavelet analysis, Whittle and local

estimators. Self-similar models of network traffic: superposition of heavy-tailed on/off

sources, FARIMA processes, Pareto Modulated Poisson Process (PMPP), Markov Modulated

Bernouli Process (MMBP), circulant embedded matrix method, Spatial Renewal Processes

(SRP), methods based on power spectrum of fractional Gaussian noise. Queueing models in

telecommunication networks: M/M/1/(K), M/D/1/(K), M/G/1/(K), G/M/1/(K), G/G/1/(K).

Generation of self-similar traffic using traditional and self-similar models.

Assessment methods Written exam (test), project work

Learning outcomes Knowledge of web development basics, including front-end as well as back-end side. Ability

to create web pages from scratch.

Required readings

1. Medhi J., Stochastic models in queueing theory. Academic Press, 2nd edition, 2002.

2. Gross D., Harris C.M., Fundamentals of queueing theory. Wiley-Interscience, 3rd edition,

1998.

3. Park, K., Willinger, W., Self-similar network traffic and performance evaluation. John Wiley

& Sons, 2000.

Supplementary

readings

1. Krishna M., Gadre V., Desai U.: Multifractal Based Network Traffic Modeling, Springer

Science & Business Media, 2003.


Course title TELEMEDICINE

Teaching method lectures, lab training, computer simulations


the course Sławomir Kocoń



Course code


Type of course compulsory Level of course master


Hours per week 4 (2L, 2Lab) Hours per semester 45 (30L, 30Lab)

69

Objectives of the

course

To provide actual knowledge on information technologies in biomedical applications and to

develop design skills in this field

Entry requirements Informatics, Computer systems, Telecommunications, Networking, Fundamentals of

Biomedical Engineering

Course contents

Lectures: Hospital and hospital information system (HIS), basic concepts of HIS on different

levels of hospital. Communication systems in healthcare. Clinical communication in

telemedicine. Electronic medical. Transfer of biomedical signals in telemedicine and its use

for stimulation devices. Internet applications in telemedicine. Reliability of health

information systems, electrical safety of medical devices and equipment. Human and

sociotechnical factors. Ethical and legal challenges. Evaluation of telemedicine systems.

Future trends in telemedicine.

Labs: Medical databases. HL7 systems. DICOM and PACS. WWW and video-conference

applications for telemedicine. Wireless transmission of biomedical signals. Biosensors

integration with Bluetooth and other modules. Wireless networks in hospitals, in

telemonitoring and teleassistance at home. Tele-service of medical equipment in hospitals


Learning outcomes

The student has increased knowledge on advanced information and communications

technologies in biomedical applications (equipment, software, specialized systems and

standards used in this field). He has practical skills useful in the area of IT&T technologies

used in e-Health regarding their development, implementation, exploitation and

assessment

Recommended

readings

1. Gordon C., Christensen J. P. (ed.): Health Telematics for Clinical Guidelines and Protocols.

IOS Press, Ohmsha, 1995

2. Mantas J. (ed.): Health Telematics Education. IOS Press, Ohmsha, 1997

3. Coiera E.: Guide to Medical Informatics. The Internet and Telemedicine. Arnold, London,

1997

4. Field M. J. (ed.): Telemedicine. A Guide to Assessing Telecommunications in Health Care.

National Academy Press, Wash. D.C., 1996

5. IT-EDUCTRA. FUNDESCO, Commission of the EC, 1998

6. Chronaki, C. E. (2004). Open ECG: Goals and achievements. Proceedings of the 2nd Open

ECG Workshop (pp. 3-4), Berlin.

7. Dolin, R. H., Alschuler, L., Boyer, S., & Beebe, C. (2004). HL7 clinical document

architecture. Release 2.0. HL7 Health Level Seven, Inc., Ann Arbor, MI. Available online

at: www.hl7.org


Course title TERAHERTZ TECHNIQUE

Field of study Electrotechnics, electronics

Teaching method Lectures in form of multimedia presentation;

project – designing, measurements and computer simulations of terahertz devices/systems


the course Przemyslaw Lopato



70

Course code

(if applicable) - ECTS points 2

Type of course Obligatory Level of course bachelor/master


Hours per week

2 hours

(lectures – 1, project – 1, other

organization is possible)

Hours per semester

30 hours

(lectures – 15,

project – 15)

Objectives of the

course

This course is intended to present a basic knowledge of terahertz technique and its

application in modern industry

Entry requirements/

prerequisites Basic course of mathematics and physics (electromagnetics)

Course contents

Generation and detection of EM waves in the THz frequency range. Passive devices in

terahertz technology. Materials properties and metamaterials in THz frequency range.

Application of terahertz technique in spectroscopy, imaging, biomedical engineering, public

safety and short-range wireless transmissions. Numerical modeling of terahertz systems.

Overview of available terahertz systems.

Assessment methods Lectures – oral exam; project – report assessment

Learning outcomes During the course, students will gain a basic knowledge of the operation, design and

modeling of measurement systems that use electromagnetic waves in the terahertz range.

Required readings 1. Yun-Shik Lee: Principles of Terahertz Science and Technology, Springer, New York 2009

2. Sakai K.: Terahertz optoelectronics, Springer, Berlin 2005

Supplementary

readings

1. Miles R. E., Harrison P., Lippens D.: Terahertz sources and systems, Kluwer, Dordrecht

2001


Course title ULTRASONIC AND RADIOGRAPHIC NONDESTRUCTIVE TESTING



Teaching method Lectures





Course code





71

Hours per week Lectures - 2 Hours per semester Lectures - 30

Objectives of the

course

This course is intended to present a unified approach to ultrasonic and radiographic

nondestructive testing.

Entry requirements/

prerequisites Mathematics, Physics

Course contents

1. Ultrasonic Principles.

2. Equipment Controls.

3. Wave Propagation.

4. Couplants, Material Characteristics, Beam Spread.

5. Attenuation, Impedance and Resonance.

6. Screen Presentations, Angle Beam Inspection with UT Calculator.

7. Transducers, Standard Reference Blocks.

8. Immersion Inspection.

9. Contact Testing, Longitudinal & Shear Waves, Snell’s Law.

10. Applications of Radiography.

11. Penetration and Absorption.

12. Radiographic Sensitivity.

13. Structure of the Atom.

14. X and Gamma Rays.

15. X-Ray Equipment.

16. Subject and Film Contrast.

17. Radiographic Film & Processing Techniques.

18. Radiation Hazard.

19. Permissible Radiation Dose.

20. Radiation Effects.

21. Protection Against Radiation.

22. Specialized Radiographic Equipment.

23. X-Ray Exposure Charts.

24. Specialized Techniques.

25. Discontinuities.

26. Practical Problem Solving.


Learning outcomes

Students will get the knowledge about Ultrasonic and Radiographic Nondestructive Testing

theory and practice. They will also know what kind of objects can be inspected with such

techniques.

Required readings

1. D. Van Hemelrijck, A. Anastassopoulos: Non Destructive Tersting, A.A. Balkema, 1996

2. http://www.ndt.org/

3. http://www.ndt-ed.org/EducationResources/CommunityCollege/communitycollege.htm

4. http://www.ndt.net/

Supplementary

readings


http://www.ndt.org/

http://www.ndt-ed.org/EducationResources/CommunityCollege/communitycollege.htm

http://www.ndt.net/

72

Course title VISUAL PROGRAMMING IN LABVIEW

Field of Study

Automatic control and robotics; Electronics and telecommunication;

Information and communications technology;

Electrical engineering.

Teaching method Lectures, demonstrations, laboratory exercises


the course dr inż. Paweł Dworak



Course code




Hours per week 1L, 2Lab Hours per semester 15L, 30Lab

Objectives of the

course

Teach students a graphical way of programming in LabVIEW. Preparation of students to the

CLAD certificate.

Entry requirements

/prerequisites Basics of programming.

Course contents

Introduction to LabVIEW environment. Navigating LabVIEW, Troubleshooting and

Debugging Vis, Implementing a VI, Developing Modular Applications, Creating and

Leveraging Data Structures, Managing File and Hardware Resources, Using Sequential and

State Machine Algorithms, Solving Dataflow Challenges with Variables, Moving Beyond

Dataflow, Implementing Design Patterns, Controlling the User Interface, File I/O Techniques,

Improving an Existing VI, Deploying an Application.

Assessment methods Continuous assessment.

Learning outcomes Students will be able to write programs in a graphical LabVIEW environment. Should be

able to pass the CLAD certification exam.

Required readings National Instruments documentation, NI forum

Supplementary

readings


73

Course title WALKING ROBOTS


Teaching method

Lectures covering basic modelling of walking robots, analysis of walking patterns and

control methods. Laboratory course covering modelling and control of a walking robot,

using simulations and miniature two-legged and multi-legged robots.





Course code


Type of course optional Level of course master

Semester Winter or summer Language of instruction english

Hours per week 1h lecture, 2h laboratory Hours per semester 15h lecture,

30h laboratory

Objectives of the

course The Student will learn to model and control a walking robot.

Entry requirements/

prerequisites Linear Control, Nonlinear Control, Basic Robotics

Course contents

Lectures cover the modelling (kinematics and dynamics) of multi-legged walking robots,

analysis of support phases, ground impacts, basic trajectory and path planning, and

nonlinear control design. Laboratory course covers simulation of walking robots and

implementation of control methods on miniature humanoid robot and multi-legged

walking robots.

Assessment methods Written exam (on last lecture), Continuous assessment during laboratory course

Learning outcomes Ability to model and control a walking robot.

Required readings 1. Chevallereau, Christine, et al., eds. Bipedal Robots: Modeling, Design and Walking

Synthesis. John Wiley & Sons, 2013.

Supplementary

readings

1. Westervelt, Eric R., et al. Feedback control of dynamic bipedal robot locomotion. Vol. 28.

CRC press, 2007.

2. Selig, Jon M. Geometric fundamentals of robotics. Springer, 2005.


faculty of electrical engineering - aktualności · artificial intelligence, patrick henry winston,...

Documents