Hybrid and distributed systems and control

Transcription

1 Hybrid and distributed systems and control Overview Introduction week DCSC September 3,

2 Team members Bart De Schutter Ton van den Boom Tamás Keviczky [ + vacancy ] + 3 postdocs + 19 PhD students 2

3 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 3

4 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)... 4

5 Model predictive control Ton van den Boom, Tamás Keviczky, Bart De Schutter, 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, Monitoring Train positions Control actions 5

6 Distributed estimation and control Tamas Keviczky, Distributed MPC coordination & cooperation 6

7 Distributed estimation and control Tamas Keviczky, 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 7

8 Multi-level and multi-agent control Bart De Schutter, Tamás Keviczky, 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 8

9 Transportation networks Bart De Schutter, Ton van den Boom, Hans Hellendoorn, 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, ) 9

10 Transportation networks Bart De Schutter, Ton van den Boom, Hans Hellendoorn, 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 10

11 Transportation networks Bart De Schutter, Ton van den Boom, Hans Hellendoorn, 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 11

12 Infrastructure networks Bart De Schutter, Hans Hellendoorn, Tamás Keviczky, 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 12

13 Hybrid and discrete-event systems Bart De Schutter, Ton van den Boom, 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 framework max: synchronization, +: durations focus on stability + analysis + control (MPC) + stochastic systems 13

14 Hybrid and discrete-event systems Bart De Schutter, Ton van den Boom, Alessandro Abate, Hybrid systems combination of continuous and discreteevent dynamics (switching) examples: electrical networks (switches, diodes), beer production, distillation column, flexible manufacturing systems, road management 14

15 Hybrid and discrete-event systems Bart De Schutter, Ton van den Boom, Hybrid systems combination of continuous and discreteevent dynamics (switching) examples: electrical networks (switches, diodes), beer production, distillation column, flexible manufacturing systems, road management various frameworks: piecewise affine, mixed-integer models, switching maxplus focus on control (MPC) and analysis, including stochastic hybrid systems 15

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