Dr.ir. Tamás Keviczky grids • Smart building control • Cooperative control of offshore wind...

Networked Cyber-Physical Systems

Dr.ir. Tamás Keviczky

Delft Center for Systems and ControlDelft University of TechnologyThe Netherlands

[email protected]://www.dcsc.tudelft.nl/~tkeviczky/

September 5, 2017 Systems & Control MSc Information Days

NCPS Team

Dr. Ir. Tamas Keviczky(Group head)

Dr. Ir. Manuel Mazo Jr.

Dr. Ir. Peyman Mohajerin Esfahani

Dr. Ir. Giulia Giordano

6 PhD students4 Post Doctoral researchers

Perspective on CPS

�= f(�, υ)

Cyber-Physical

Collision Avoidance

Combustion Control

ABS/ESP

CAN/FlexRay

dx/dt = f(x,u)

Networked CPS

September 5, 2017 5

Zoo of Systems

Interconnection

(Sub)systemdynamics

COMPLEXITY

CO

MP

LEX

ITY

The Challenge of Distributed Control

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?????

Optimization and Team Decision Making

How can we distribute optimal team decision-making?

How can this work in a real-time control system?

What information should be exchanged and when?

What is the impact of the communication topology?

…

Pick an MSc project

in Networked Cyber Physical Systems

1. Increased autonomy via embedded, real-time optimization-based solutions for control and estimation

Research Agenda

Utilize problem structure, parallel computing,for real-time solutions in a closed feedback loop

Subsystem interactions(dynamics, objective, constraints)

Componentsubsystems

2. Distributed decision-making for interconnected systems in an optimization-based framework

Research Agenda

Distributed optimization as a paradigm fordistributed control and decision-making

Subsystem interactions(dynamics, objective, constraints)

Componentsubsystems

3. Decision-making under uncertainty

Research Agenda

Scalability/ComputationUncertainty/InformationDynamic nature

Control Theory

Applied Probability

Optimization

Interdisciplinary solutions

MSc projects

Security-aware Control Synthesis in Networks

• Your are a white-hat hacker!

• Game between the system operator and the attacker

• Mimic natural system behaviors while maximally damage

the system!

• How to mitigate such a damage

Sustainable Buildings: an Advanced Diagnosis Approach

• Modeling the building dynamics

• Design filter to identify certain abnormalities

• Validate the performance through the real measurements

Joint project with Dwa (www.dwa.nl)

Dynamical System Filter

©DWA

4. Control under communication constrains

Research Agenda

Event-based control advances: Modelling of traffic, Security, Implementations, …

5. Correct-by-design synthesis of controllers

Research Agenda

Population

+

b

x

cb

a+a

Genetic operatiors

Fitness assessmentand parent selection

Controller

User-defined grammar

Formal verification

#1

#2

Temporal logicproperties

Formal methods in control: Abstraction/refinement, Symbolic regression, SMT…

Talk onThursday

6. Networked systems

Research Agenda

Network-decentralised control, coordination and estimation

Network-decentralized height/position estimation for cartography: infer a global map based on local information exchanges.

Network-decentralised coordination of robots with collision avoidance.

Interacting dynamic subsystems with local information and local action

6. Networked systems

Research Agenda

Structural analysis of biological systems

Natural and biological systems global behaviour (complex interplay of local interactions) astoundingly robust to environmental changes, fluctuations and perturbations.

• “Verification” of structural properties: given a graph structure, generaterandom functions that satisfy the assumptions and check that the property always holds.

• Simulation-based/analytical study of biological systems and chemical reaction networks.

Structural analysis: assess whether a class of systems always enjoys a given property, due to its structure (topology of the interaction graph) and not to specific parameter values.

Automotive and Mobile Robot Applications• Vehicle platooning

– Nonlinear trajectory planning (driver assist, traffic constraints)

– Optimize fuel economy, ride comfort– Optimize communications– Verifiable Safety

• Driving on the limits of handling

– Autonomous driving, complex vehicle dynamics

– Exploit problem structure to enable real-time computations

• Distributed Robotic Networks

– Connectivity maximization– Distributed estimation,

SLAM in active sensor networks– Emergent behaviours

Aeronautical and Space Applications

• Reconfigurable fault-tolerant predictive flight control

– Real-time, verifiable computation of constrained optimal control laws

– Online optimization-based robust fault estimation for constrained nonlinear systems

• Satellite proximity operations

• Distributed control of spacecraft formations and swarms

Large-Scale Infrastructure Applications

• CPS security and privacy

• Wireless efficient control

• Demand side management

• Distributed control of water/power networks

• Distributed stochastic MPC of Aquifer Thermal Energy Storage smart grids

• Smart building control

• Cooperative control of offshore wind farm power networks

Canal networkHydro power network

September 5, 2017 22

Zoo of Systems

Interconnection

(Sub)systemdynamics

COMPLEXITY

CO

MP

LEX

ITY

Real-Time Nonlinear Trajectory PlanningFor Long Heavy Truck Combinations

• Exploit problem structure to enable real-time computations

• Serve as a driver assist system and in future autonomous driving solutions

MScProject

• Respect vehicle dynamics and constraints imposed by the truck and the environment

• Optimize fuel economy, ride comfort, etc.


Zoo of Systems

Interconnection

(Sub)systemdynamics

COMPLEXITY

CO

MP

LEX

ITY


Reconfigurable Control Design inAerospace Applications

• Integrated fault detection, isolation, and predictive control design

• Real-time and verifiable computation of constrained optimal control laws

• Improve penetration of state-of-the-art methods into industrial practice

MScProject


Zoo of Systems

Interconnection

(Sub)systemdynamics

COMPLEXITY

CO

MP

LEX

ITY


Multi-Agent Systems

Different agents (e.g. robots, spacecraft) have to collaborate

autonomously in order to reach a common goal

Organic Air Vehicle Formation Flight


Distributed Control and FDIR Design for Satellite Formations

MScProject

Delfi-C3

• Individual satellites are tightly coupled by performance requirement

• FDIR is critical for mission success

• Single central computing unit is undesirable

• Collaboration with ongoing space projects at Aerospace Faculty (e.g. Delfi nanosat)


Cooperative IndoorFormation Flight Control

• Cooperating quadrotor fleet

• Sensor network-based indoor localization scheme

• Coupled dynamics and control task of lifting and transporting a hung mass

• Optimal synchronization problem with constrained subsystem dynamics

• Implementation in Networked Embedded Robotics Lab

MScProject

In collaboration with LR, Micro Air Vehicle Group (Bart Remes, Christoph De Wagter)

Check out the recent IMAV competitions!!!


Distributed Control of Multi-Agent Systems on a Mobile Robot Testbed

MScProject

http://distributedroboticslab.blogspot.com

iRobot CreateCricket RF-USrange sensor

Networked Embedded Robotics Lab


Zoo of Systems

Interconnection

(Sub)systemdynamics

COMPLEXITY

CO

MP

LEX

ITY


Distributed Optimization and MPC for Large-Scale Infrastructures

• Decomposition methods in optimization and dynamic programming

• Application to Distributed MPC schemes

• Study of performance versus uncertainty in DMPC schemes

• Achievable performance bounds

MScProject

Canal network

Traffic network

Hydro power network


Distributed Optimization and MPC for Large-Scale Infrastructures

• Decomposition methods in optimization and dynamic programming

• Application to Distributed MPC schemes

• Study of performance versus uncertainty in DMPC schemes

• Achievable performance bounds

MScProject

Distributed Optimization and MPC forHigh-Performance Buildings

MScProject


Exploit Problem Structure toReduce Complexity of Control Design

• Enable control design for large-scale systems by exploiting symmetry in

– interconnection– subsystem dynamics

• Construct distributed (structured) controllers, estimators

• Respect global objectives and analyze performance of distributed solution

MScProject


Distributed Constraint Fulfillment

• Design methods for coupled constraints (e.g. collision avoidance)

• Guaranteed feasibility in distributed MPC schemes

• Approximation schemes, controlled invariant sets and reachability

• Robust constraint fulfillment with negotiation

• Reducing conservativeness

MScProject


Consensus inDistributed Predictive Control

• Interplay between consensus seeking and MPC

• Incremental subgradient methods

• Optimal synchronization problems with constrained subsystem dynamics

• Application to multi-vehicle coordination, oscillator networks, etc.

MScProject


Distributed Moving Horizon Estimation

• Linear and nonlinear distributed solutions for dynamic systems

• Approximation of arrival cost with local particle filters

• Respecting physical constraints

• Local unobservability, information exchange with neighboring sensors

MScProject


Some Recommended Courses

• SC42095 Digital Control

• SC42010 Robust and Multivariable Control Design

• SC42040 Adaptive and Predictive Control

• SC42055 Optimization in Systems and Control

• WI4218 Convex Optimization and Semi-Definite Programming

• SC42100 Networked and Distributed Control Systems

• SC42075 Modeling and Control of Hybrid Systems

• SC42060 Modeling and Nonlinear Systems Theory

• AE4-305 (Spacecraft Attitude Dynamics and Control)


Preparation for Control Theory Course

• Refresh linear algebra knowledge(see material also on Brightspace)

• Order textbook(B. Friedland, Control System Design – An Introduction to State-Space Methods)

Dr.ir. Tamás Keviczky grids • Smart building control • Cooperative control of offshore wind...

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