CONTROL OF GANTRY CRANE SYSTEM BASED ON FUZZY LOGIC

TECHNIQUE

AZLIA BINTI ABDUL RAHMAN

A project report submitted in partial fulfilment of the

requirements for the award of the degree of

Master of Engineering (Electrical – Mechatronics and Automatic Control)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

JANUARY 2013

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To my beloved family, lecturers and friends who have given me a lot of support and

encouragement. Thank you so much.

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ACKNOWLEDGEMENT

Alhamdulillah, I am greatly indebted to Allah SWT for His blessings and His

power.

I would like to take this opportunity to express my gratitude to my project

supervisor, Dr. Abdul Rashid bin Husain for guiding & giving me lots of idea in

order to complete this project.

Support and technical assistant from the industry sector from Siemens

Malaysia SDN. BHD, Mr. Amiruddin Zahamail, which support me throughout these

thesis should also be recognized for his sponsorships – he has provided assistance at

various occasions and technical supports. His brilliant ideas and opinion are very

useful.

Last but not least, I would like to give a special thanks to my parent and

family for their love, understanding, support and bless. I really love them so much.

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ABSTRACT

Gantry cranes are widely used in industry for transporting heavy loads and hazardous

materials in shipyards, factories, nuclear installations, and high building construction.

The crane should move the load as fast as possible without causing any excessive

movement at the final position. However, most of the common gantry crane results in

a swing motion when payload is suddenly stopped after a fast motion. The swing

motion can be reduced but will be time consuming i.e. reduce the facility availability

as well as productivity. Moreover, the gantry crane needs a skilful operator to control

manually based on his or her experiences to stop the swing immediately at the right

position. Furthermore to unload, the operator has to wait the load stop from

swinging. The failure of controlling crane also might cause accident and may harm

people and surrounding. To overcome this problem, an intelligent gantry crane

system had been introduced. Fuzzy logic controllers is proposed, designed and

implemented for controlling payload position as well as the swing angle of the gantry

crane. PID control approach will be taken as comparator based on the previous

research. This project is to propose the control design of AC Servo drive system for

linear guide application of gantry crane. The typical linear guide applications can be

hoist system like crane, lift, gantry crane system. In this proposed control design, the

main purpose of controlling gantry crane system is transporting the load as fast as

possible to the required position with precision, without any force disturbance and

parameter variations which is swing motion which cause a steady and/or transient

error in the conventional ac servo drive system. Basically this system is designed

according to the experimental results which convinced the collected data obtained,

and simulation approach.

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ABSTRAK

Kren gantri digunakan secara meluas dalam industri untuk mengangkut beban berat

dan bahan-bahan berbahaya di limbungan kapal, kilang, pepasangan nuklear, dan

pembinaan bangunan tinggi. Kren harus bergerak secepat mungkin tanpa

menyebabkan mana-mana pergerakan yang berlebihan di kedudukan terakhir. Walau

bagaimanapun, yang paling biasa kren gantri bermasaalah dalam gerakan ayunan

apabila muatan tiba-tiba dihentikan selepas gerakan pantas. Sudut ayunan boleh

dikurangkan tetapi akan memakan masa iaitu mengurangkan adanya kemudahan

serta produktiviti. Selain itu, kren gantri memerlukan pengendali mahir untuk

mengawal secara manual berdasarkan pengalaman beliau untuk menghentikan

ayunan segera di kedudukan yang betul. Tambahan pula untuk memunggah,

pengendali telah menunggu hentian beban dari buaian. Kegagalan mengawal kren

juga mungkin menyebabkan kemalangan dan boleh membahayakan orang dan

sekitarnya. Untuk mengatasi masalah ini, pintar gantri kren sistem telah

diperkenalkan. Fuzzy logik adalah dicadangkan, direka dan dilaksanakan untuk

mengawal kedudukan muatan serta sudut swing kren gantri. Pendekatan kawalan

PID akan diambil sebagai comparator berdasarkan penyelidikan sebelumnya. Projek

ini adalah untuk mencadangkan reka bentuk kawalan AC sistem pemacu servo untuk

aplikasi panduan linear gantri kren. Panduan tipikal aplikasi linear boleh angkat

sistem seperti kren, lif, sistem gantri kren. Dalam reka bentuk kawalan yang

dicadangkan ini, tujuan utama sistem kren gantri mengawal dan mengangkut beban

secepat mungkin pada kedudukan yang dikehendaki dengan tepat, tanpa gangguan

mana-mana angkatan dan variasi parameter yang merupakan gerakan ayunan yang

menyebabkan kesilapan yang mantap dan / atau fana dalam ac konvensional servo

drive sistem. Pada asasnya, sistem ini direka mengikut kepada keputusan eksperimen

yang membuktikan data yang dikumpul diperolehi, dan pendekatan simulasi.

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TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENTS iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xiii

LIST OF SYMBOLS xiv

LIST OF APPENDICES xv

1 INTRODUCTION 1

1.1 Introduction 1

1.2 Objectives 3

1.3 Scope of Project 3

1.4 Methodology 4

1.5 Thesis Outline 6

2 MODELLING OF THE GANTRY CRANE SYSTEM 7

2.1 Introduction 7

2.2 Literature Review 9

2.3 Model Description 11

2.4 Derivation of the Equation of Motion 12

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3 FUZZY LOGIC CONTROLLER 18

3.1 Introduction of Fuzzy Logic Control 18

3.1.1 Fundamentals of Fuzzy Logic Control 19

3.2 Fuzzy Logic Control System 21

3.3 Fuzzy Logic Controller Design

for Gantry Crane 22

3.3.1 Control Structure 22

3.3.2 Fuzzification and Inference 29

3.3.3 Defuzzification 30

4 SIMULATION RESULTS AND ANALYSIS 32

4.1 Introduction 32

4.2 Simulation 32

4.2.1 Dynamic Model of Gantry Crane

in SIMULINK 38

4.3 Results and Analysis 41

5 EXPERIMENTAL SETUP 47

5.1 Introduction 47

5.2 Hardware Implementation 47

5.3 Software Implementation 50

5.3.1 Simatic Step7 Software 50

5.3.2 FuzzyControl++ V5.0 Software 54

5.3.2.1 Fuzzy System Design 54

5.4 Experimental Results and Analysis 54

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6 CONCLUSION 66

6.1 Future Works 66

6.2 Conclusion 67

REFERENCES 68

Appendix A 71

Appendix B 80

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LIST OF TABLES

TABLE NO. TITLE PAGE

2.1 Summary of Literature Review 9

4.1 Numerical Values of AC Servo Motor Model 38

4.2 Position Control Performance 42

4.3 Swing Angle Control Performance 44

5.1 Lab-scale of Gantry Crane Parameter Values 48

5.2 Comparison of Simulation and Experimental Results 65

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LIST OF FIGURES

FIGURE NO. TITLE PAGE

1.1 Flow Chart of Project Methodology 5

2.1 Model of Gantry Crane System 11

3.1 General Fuzzy Control System 19

3.2 The Fuzzy Control Rule Base 20

3.3 Block Control of Fuzzy Control System 21

3.4 Block Diagram of Gantry Crane System 22

3.5 Principle of Fuzzy Logic Control 24

3.6 Antecedents of Gantry Crane System 24

3.7 Fuzzy Controller Structure 24

3.8 Membership functions of position control 26

3.9 Membership functions of swing angle control 27

4.1 FIS Editor for Position Control 33

4.2 Membership Function of Input Error for Position Control 33

4.3 Membership Function of Input Error Rate

for Position Control 34

4.4 Membership Function of Output Voltage for Position Control 34

4.5 FIS Editor for Swing Angle Control 35

4.6 Membership Function of Input Error for Swing Angle Control 35

4.7 Membership Function of Input Error Rate

for Swing Angle Control 36

4.8 Membership Function of Output Voltage

for Swing Angle Control 36

4.9 Rules for Position Control 37

4.10 Rules for Swing Angle Control 37

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4.11 Dynamic System of Overall View of Gantry Crane Model 39

4.12 Fuzzy Logic Controller for Position and

Swing Angle Applied on Gantry Crane Model 39

4.13 Dynamic System of Gantry Crane and AC Servo Motor 40

4.14 Comparison of Position Control Output Response

for Fuzzy and PID Controller 41

4.15 Comparison of Swing Angle Control Output Response

for Fuzzy and PID Controller 43

4.16 Fuzzy Logic Control Surface Behavior of Position Control 44

4.17 Fuzzy Logic Control Surface Behavior of Swing Angle Control

45

4.18 VRML Animation of Gantry Crane System

via 3-D Visualization

46

5.1 Lab-scale Gantry Crane System 48

5.2 Digital and Analogue Inputs Outputs Connection 49

5.3 Integration Software and Hardware System

for Lab-scale Gantry Crane 50

5.4 Programming Data Blocks in Step 7 for PLC S7-300 52

5.5 Function Blocks Used in Simatic Step 7 52

5.6 Programming Configuration in Simatic Step 7 53

5.7 STL Structure Programming in Simatic Step 7 53

5.8 Fuzzy Logic Controller Design for Position Control

via FuzzyControl++ V5.0 Software Toolbox 57

5.9 Fuzzy Logic Controller Design for Swing Angle Control

via FuzzyControl++ V5.0 Software Toolbox 59

5.10 Singleton Functions 60

5.11 Control Behaviors Performance of Fuzzy Control System for

Position Control in FuzzyControl++ V5.0 Software 62

5.12 Control Behaviors Performance of Fuzzy Control System

for Swing Angle Control in FuzzyControl++ V5.0 Software 63

5.13 Output Responses of Velocity and Error for Position and

Swing Angle Control 64

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LIST OF ABBREVIATIONS

PLC - Programmable Logic Controller

FLC - Fuzzy Logic Controller

FB - Function Block

PID - Proportional-Integrator-Derivative

PD - Proportional-Derivative

AC - Alternate Current

VRML - Virtual Reality Modeling Language

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LIST OF SYMBOLS

- Exponention friction factor

- Motor damping coefficient

- Viscose friction coefficient

- Coulomb friction coefficient

- Maximal static friction

- Load inertia

- Motor inertia

- Maximal amplifier current

K - Motor gain

- Gear stiffness factor

- Inductance of magnetizing circuit

n - Gear transmission

- Resistance of magnetizing circuit

- Motor starting torque backlash

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LIST OF APPENDICES

APPENDIX TITLE PAGE

A Configuration of FuzzyControl++ and Simatic Step7 71

B Data Sheet of 9400 AC Servo High Line Lenze 80

CHAPTER 1

INTRODUCTION

1.1 Introduction

This project is basically designing and implementing fuzzy logic control to

control payload position as well as the swing angle for an intelligent gantry crane

system. Throughout the world, there have been many researches about the concept

and implementation of this system which is deemed suitable for all types of control

applications. For this project, the implementation of fuzzy logic control is applied to

a gantry crane model to overcome and improve the performance level from other

controllers approach proposed such as PD and PID, which is been said that they have

higher steady state error and low sensitivity to disturbance. The fuzzy logic

controllers were designed based on information of the skillful operators and without

the need of crane model and its parameters [5]. The performance of the proposed

intelligent gantry crane system had been evaluated based on simulation and

experimentally on a lab-scale gantry crane system.

In this project, AC Servo drive system is been introduced to control the linear

guide which is application of gantry crane. When people talk about servo drives

today, they generally mean highly dynamic three-phase drives. Servo drives

primarily perform positioning tasks in tooling machines, manipulators or robots. But

these ac servo drive system are increasingly finding their way into printing machines,

conveyor belts and cutting machinery where precise positioning or angular

synchronism are required. Here, servo converters, motors with sensor technology

2

and mechanical transfer elements form an extremely integrated system whose

components have to be seen as a single entity. Because of the low cost, high

reliability, power efficiency, and easy maintenance, induction and permanent-magnet

AC motor drives have been widely used in industrial applications, which stimulate

research in its motion control to achieve high performance.

The development of fuzzy logic control design is implemented using fuzzy

logic toolbox in Matlab Simulink. The main features of the fuzzy logic design

process consist of the development of input and output of the membership functions.

In the case of gantry crane, error and error rate of position and swing angle are taken

into consideration as an input. Meanwhile, the voltage is taken as an output. Since

there is no specific form to be used when designing fuzzy logic control, thus, the

basic triangle and trapezoidal forms are chosen for input and output membership

functions [17]. In most cases, the performance of fuzzy control is minimally

influenced by the shapes of memberships, but mainly by the characteristics of control

rules.

As for the hardware part, it consists of many parts of mechanical sub-system,

an actuation mechanism for transferring payload, position and swing angle sensors,

real-time control software/hardware. PLC S7-300 (Siemens) model is used as

controller mechanism to control AC Servo drive system which attached to the linear

guide for positioning of gantry crane in with the payload is connected. Two sensors

are used to measure linear guide position and payload swing angle. For this lab scale

gantry crane, a planar movement with fixed cable, length of cable and fixed load is

been considered. The experiment will be run based on the fuzzy controlled

parameters setting.

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1.2 Objectives

The main objective of this project is to design and implement fuzzy logic

control in order to control payload position as well as the swing angle for an

intelligent gantry crane system. The objectives can be narrowed to many intentions :

(i) To design the control algorithm for planar gantry crane system by using fuzzy

logic controllers to control the payload position to be moved to the desired

position while payload swing angle will be kept asymptotically small at final

position.

(ii) To develop simulation for the proposed system.

(iii) To implement the proposed control method based on the VRML animation

and lab scale gantry crane design based on experimental and compare the

result effectiveness with classical PID controllers approach.

1.3 Scope of Project

This project is a combination of hardware and software parts development to

implement the fuzzy logic control method on gantry crane system. For the software

part, MATLAB Simulink software is chosen to program and simulate the fuzzy logic

controller and apply to the gantry crane system.

The scopes of project for software are :

i. Literature study on the most appropriate programming and toolbox in

Matlab Simulink for simulation of proposed gantry crane model.

ii. Analyze and study on how to design a fuzzy logic controller.

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iii. Apply fuzzy logic controller algorithm to the developed model of gantry

crane in Matlab Simulink.

iv. Run the simulation and design in VRML animation and fix the error.

v. Interface the software and hardware part by using Simatic Net Software to

communicate FuzzyControl++ and Programmable Logic Controller

(PLC) from Siemens. The programming for the PLC is been done using

Simatic S7 PLC (SIEMENS).

1.4 Methodology

In order to meet the objectives of the project, the system is designed based on

several steps of approach which to optimize the anti-swing and zero steady state error

performance of gantry crane system. The methodology to complete this project will

be done on simulation and experiment evaluation. The control method proposed is

Fuzzy logic control (FLC). Fuzzy logic controller will be compared with PID

controller from previous researches, which the existing mathematical model

development will be applied for ac servo and gantry crane. The proposed FLC is

based on fuzzy algorithm and the fuzzy rules developed.

The proposed controller consists of fuzzy logic controllers for both position

and anti-swing control respectively. The objective of the proposed fuzzy logic

controllers is to control the payload position X(s) so that it moves to the desired

position Xref(s) as fast as possible without excessive swing angle of the payload θ(s).

Here, the design of fuzzy logic control is based on a heuristic approach. Figure 1.1

below shows the flow chart of project methodology.

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Figure 1.1 : Flow Chart of Project Methodology

Identify & analyze gantry crane problem - swing motion

Study on gantry crane control method - PID & Fuzzy

Develop mathematical model for system

Design Fuzzy Logic Controller (based heuristic)

Implement Simulation to perform control methods- Matlab/Simulink

and program to PLC

Design improvement lab-scale for gantry crane + system

integration (software)

Run experiment to perform control methods

Evaluate & compare performance of output from

simulation & experiment

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1.5 Thesis Outline

This thesis consists of six chapters. Chapter 1 is about the introduction,

objectives, scope of project and methodology. The purpose is to give a brief

overview of this project.

Chapter 2 defines and illustrates the steps employed in the fuzzy logic

controller. Including detailed about modeling and derivation of equations for the

gantry crane system. All these methodology should be followed for a better

performance.

Chapter 3 is the fuzzy logic controller. This chapter provides a theory of

fuzzy logic, the fuzzy logic control system, fuzzy logic control design and

application of fuzzy control to a gantry crane. It describes about research and

information about the project, which every fact found through the journals or other

references, will be compared and the better methods have been chosen for the

project.

Chapter 4 shows the details of designing a controller and dynamic system in

simulation Matlab/Simulink and VRML animation. It also describes the analysis of

project findings. The results are presented by the transient response of the output

performance.

Chapter 5 describes about the implementation of experimental on lab-scale of

gantry crane in terms of software and hardware parts.

Chapter 6 provides the conclusion and some suggestion for future works for

this project.

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[2] M.A.Ahmad, M.S. Ramli, R.M.T. Raja Ismail, A.N.K. Nasir and M.A.

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Input Shaping for Anti-Sway Control of a Gantry Crane System, Conference

on Innovative Technologies, 2009.

[3] Chunshien Li and Chun-Yi Lee, Fuzzy Motion Control of an Auto-

Warehosuing Crane System, IEEE Trans. Industrial Electronics, vol. 48, no.

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[4] Yaolong Tan, Jie Chang, and Hualin Tan, Adaptive Backstepping Control

and Friction Compensation for AC Servo with Inertia and Load Uncertainties,

IEEE Trans. Industrial Electronics, vol. 50, no. 5, October 2003.

[5] Wahyudi and J.Jalani, Robust Fuzzy Logic Controller for an Intelligent

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[6] Mohd Ashraf, Ahmad Nor and Haszuraidah, Techniques of Anti-Sway and

Input Tracking Control of Gantry Crane System, International Conference

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Research Center for Communications and Information Technology,King

Mongkut’s Institute of Technology,Thailand, 2000.

[9] Karel Jezernik, High Precision VSS Motion Control of Servo Drives,

International Journal of University of Maribor, Faculty of Electrical

Engineering and Computer Science, 2002

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.

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[21] Simatic S7 Fuzzy Control User’s Manual, Siemens.

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[23] L-Force Loader User’s Manual, Lenze, 2003.