hybrid, adaptive, and nonlinear systems · pdf fileexamples: queuing lines in ... road...

Hybrid, adaptive, and nonlinear systems

Overview

Introduction week DCSC

September 5, 2017

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

+ 3 postdocs/reseachers

+ 12 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 and predictive control (SC42040)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 Shu Lin: Modeling and control of large-scale urban traffic networks

I Xiaojie Luan: Train scheduling and maintenance planning

I Yashar Zeinaly (*): Multi-level control of large-scale logistic systems

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

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


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 in railwayinfrastructure 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 · pdf fileexamples: queuing lines in ... road...

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