hybrid, adaptive, and nonlinear systems center for...simone baldi erik steur sergio grammatico...

Hybrid, adaptive, and nonlinear systems

Overview

Introduction week DCSC

September 4, 2018

Hybrid, adaptive, and nonlinear 1 / 22

Overview

Hybrid, adaptive, and nonlinear systems

Team members

Main research topics & ongoing work

My own work

Related courses

Ongoing research

Selected MSc project proposals


Team members

Bart De SchutterTon van den BoomSimone BaldiErik SteurSergio GrammaticoNathan van de WouwJoris Sijs

+ 2 postdocs/reseachers

+ 13 PhD students


Objectives and research area

Development of systematic methods to analyze, monitor, and controlcomplex systems, in particular

I nonlinear systemsI hybrid systems, i.e. systems with continuous and discrete-event

behavior (switching)I large-scale systems and networks consisting of interacting subsystems

Multi-level control with coordination within and across all levels

Adaptive solutions for control of uncertain systems

Focus on both fundamental research and target applications: smarttransportation and smart infrastructure in smart cities, biochemicalcircuits


Main research topics

Model predictive control

Multi-level and multi-agent control

Hybrid and discrete-event systems

Adaptive and reconfigurable systems

Nonlinear systems

Big data

Game theory

. . .

Transportation networks (rail, road)

Infrastructure networks (water,energy, logistics)

Smart buildings

Biochemical circuits

. . .

measurements

model

optimization

prediction

actionscontrol

objective,constraints

systeminputs

control

MPC controller


Model predictive control

Ton van den Boom, Bart De Schutter, . . .


Multi-level and multi-agent control

Bart De Schutter, Sergio Grammatico, . . .

Divide system along various temporal and spatial scales

Multiple control layers, intelligent control agents

Objective: coordination within and across all layers

Methods: MPC, game-based methods, ant colony optimization

small region

large region

supervisor supervisor

localcontroller controller

localcontroller

local

high−level supervisor

fast dynamics

slow dynamics



Bart De Schutter, Ton van den Boom, . . .

Discrete-event systems

Event-driven: state changes due tooccurrence of event

Examples: queuing lines in supermarket,manufacturing system, railway network

max-plus algebra as main modelingframework

max: synchronization, +: durations

Focus on control (MPC) + analysis +stochastic systems




Hybrid systems

Combination of continuous anddiscrete-event dynamics (switching)

Examples: electrical networks (switches,diodes), beer production, distillationcolumn, flexible manufacturing systems,road management

.T=f (T,w)

off

on mode

T=f (T,w)

off mode

T < Tlow

T > Tupp

.on




Hybrid systems

Combination of continuous anddiscrete-event dynamics (switching)

Examples: electrical networks (switches,diodes), beer production, distillationcolumn, flexible manufacturing systems,road management

Various frameworks: piecewise affine,mixed-integer models, switching max- plus

Focus on control (MPC) + analysis +stability + stochastic systems

−4−2

02

4

−4−2

02

40

2

4

6

x1

x2

PW

A( x

1, x

2)


Adaptive and reconfigurable systems

Simone Baldi, . . .

Adaptation and reconfigurationcapabilities in control systems

Focus on problems where model-basedapproaches are at stake due to lack ofknowledge (uncertainties in systemand/or environment, faults, . . . )

→ adaptively drive the system towarddesired behavior

Reconfigurable control systems (detectfaults and/or changes in operatingconditions)

→ automatic reconfiguration withouthuman intervention, reducemaintenance costs


Transportation networks


Freeway and urban traffic networksI traffic jams & congestion → time losses, costs,

incidents → dynamic traffic managementI integration of various control measures (speed

limits, ramp metering, route guidance, . . . )




Freeway and urban traffic networksI integration of various control measures (speed

limits, ramp metering, route guidance, . . . )I integration of freeway & urbanI sustainable mobility: reduction of emissions

and fuel consumptionI multiple objectives – balance between user &

system optimumI large-scale traffic networks




Intelligent vehiclesI automated highway systems

→ hierarchical controlI cooperative intelligent vehicle highway

systems + cybercars→ distributed and multi-level control

Railway networksI operational managementI (re)schedulingI preventive maintenanceI service contracting


Infrastructure networks

Bart De Schutter, . . .

Water networksI flood preventionI irrigation

→ maintain water levels withinbounds

Electricity networksI smart gridsI energy hubs (gas/electricity)

Logistic systemsI baggage handlingI container terminals

→ routing and scheduling


Smart buildings

Simone Baldi, . . .

Energy efficiency: climatecontrol

Building automation:monitor and manageloads

Optimized maintenance:I detection and

identification of faultsI . . .

Challenges: address occupants’ behavior, time-varying loads, weatherconditions, uncertain building parameters, . . .


Ongoing work

Distributed and multi-level control of large-scale hybrid and discrete-event systems

Keep on increasing speed and performance of analysis and controlmethods

Increasing emphasis on mixed-integer optimization

Bridging gap computer sciences – systems and control

Smart cities


Recommended courses

Systems & Control courses:I optimization in systems and control (SC42055)I modeling and control of hybrid systems (SC42075)I adaptive control (SC42120)I model predictive control (SC42125)I knowledge based control systems (SC42050)I networked and distributed control systems (SC42100)I . . .

Application courses (see list on DCSC website), e.g.:I traffic & transportation (MSc Transport, Infrastructure & Logistics) —

Profile Transportation NetworksI optimization, stochastic systems (MSc Mathematics)I . . .


Ongoing research — PhD students and postdocs

Traffic and transportationI Jose Ramon Domınguez Frejo: Efficient traffic control with variable

speed limits

I Anahita Jamshidnejad: Multi-level predictive traffic control forlarge-scale urban networks

I Xiaojie Luan: Train scheduling and maintenance planning

EnergyI Farid Alavi: Robust control of fuel-cell-car-based smart energy systems

I Jesus Garcia Lago: Development of non-intrusive and intrusive energymanagement algorithms

I Miguel Picallo Cruz: Advanced monitoring and control of the electricaldistribution grid

I Tomas Pippia: Robust management and control of smart multi-carrierenergy systems

I Jiangeng Fu: Big data methods for maintenance of smart energysystems


Ongoing research — PhD students and postdocs

FundamentalsI Erwin de Gelder: Big data approach for scenario-based assessment of

automated driving systems

I Amir Firooznia (*): Integrated distributed control of cyber-physicalsystems

I Zhou Su (*): Game-theoretic approaches for service contracting inrailway infrastructure maintenance

I Jia Xu (*): Model predictive control for hybrid systems


Cooperation with companies

Some companies you can do your MSc project with/at:

TNO

Infraspeed

ProRail

Oce

Technolution

Mobile Water Management

ORTEC

Ministry of Transportation – DVS

. . .


For more information . . .

See web site: www.dcsc.tudelft.nl/~bdeschutter →Research

Contact PhD students and other researchers & professorsinvolved (see slides 6–16 and 19–20)


hybrid, adaptive, and nonlinear systems center for...simone baldi erik steur sergio grammatico...

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