Hybrid and distributed systems and control · •Freeway and urban traffic networks integration of...
Transcript of Hybrid and distributed systems and control · •Freeway and urban traffic networks integration of...
1Hybrid and distributed systems and control
Hybrid and distributedsystems and control
Overview
Introduction week DCSC
September 3, 2013
2Hybrid and distributed systems and control
Team membersBart De SchutterTon van den BoomTamás Keviczky[ + vacancy ]
+ 3 postdocs
+ 19 PhD students
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Objectives and research area• Development of systematic methods to analyze, monitor, and
control complex large-scale systems consisting of interacting subsystems
• Inclusion of hybrid aspects (i.e. continuous and discrete-event behavior – switching)
• Distributed and multi-level control with coordination within and across all levels
• Focus on both fundamental research and target applications
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Main research topics
• Model predictive control• Distributed estimation and control• Multi-level and multi-agent control• Hybrid and discrete-event systems • ...
• Transportation networks (rail, road)• Infrastructure networks (water,
energy, logistics)• ...
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• Control approach based on prediction (via model) and optimization
• Nonlinear and robust MPC• MPC for (switching)
max-plus-linear systems• Efficient implementation• Large-scale systems
• Main applications:railway & road traffic,infrastructure,robotics, …
Model predictive controlTon van den Boom, Tamás Keviczky, Bart De Schutter, …
Monitoring
Train positions
Controlactions
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Distributed estimation and control
• Distributed MPC→ coordination &
cooperation
Tamas Keviczky, …
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Distributed estimation and control
• Focus on problems where centralized solutions are prohibitive too expensive to implement, not feasible computationally not feasible due to communication constraints
• Develop systematic design methods to distribute and coordinate the global optimization problem among local controllers
• Exploit problem structure whenever possible
• Main design philosophy relies on solving local problems based on models of neighbors respecting limited communication
Tamas Keviczky, …
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Multi-level and multi-agent control
• 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
Bart De Schutter, Tamás Keviczky, …
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Transportation networks
• Freeway and urban traffic networks traffic jams & congestion → time losses, costs,
incidents → dynamic traffic management integration of various control measures (speed
limits, ramp metering, route guidance, …)
Bart De Schutter, Ton van den Boom, Hans Hellendoorn, …
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Transportation networks
• Freeway and urban traffic networks integration of various control measures
(speed limits, ramp metering, traffic signals, route guidance, …)
integration of freeway & urban sustainable mobility: reduction of emissions
and fuel consumption multiple objectives – balance between user &
system optimum large-scale traffic networks
Bart De Schutter, Ton van den Boom, Hans Hellendoorn, …
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Transportation networks
• Intelligent vehicles automated highway systems
→ hierarchical control cooperative intelligent vehicle
highway systems+ cubrecars→ distributed and multi-level control
• Railway networks operational management (re)scheduling preventive maintenance service cointracting
Bart De Schutter, Ton van den Boom, Hans Hellendoorn, …
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Infrastructure networks
• Water networks: flood prevention irrigation
→ maintain water levels within bounds
• Electricity networks: smart grids energy hubs (gas/electricity)
• Logistic systems: baggage handling container terminals → routing and scheduling
Bart De Schutter, Hans Hellendoorn, Tamás Keviczky, …
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Hybrid and discrete-event systems
• Discrete-event systems event-driven: state changes due to
occurrence of event examples: queuing lines in supermarket,
manufacturing system, railway network max-plus algebra as main modeling
frameworkmax: synchronization, +: durations
focus on stability + analysis + control (MPC) + stochastic systems
Bart De Schutter, Ton van den Boom, …
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Hybrid and discrete-event systems
• Hybrid systems combination of continuous and discrete-
event dynamics (switching) examples: electrical networks (switches,
diodes), beer production, distillation column, flexible manufacturing systems, road management
Bart De Schutter, Ton van den Boom, Alessandro Abate, …
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Hybrid and discrete-event systems
• Hybrid systems combination of continuous and discrete-
event dynamics (switching) examples: electrical networks (switches,
diodes), beer production, distillation column, flexible manufacturing systems, road management
various frameworks: piecewise affine, mixed-integer models, switching max-plus
focus on control (MPC) and analysis, including stochastic hybrid systems
Bart De Schutter, Ton van den Boom, …