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Control over Communication Networks: Modeling, Analysis, and Design of Networked Control Systems and Multi-Agent Systems over Imperfect Communication Channels

✍ Scribed by Jianying Zheng, Liang Xu, Qinglei Hu, Lihua Xie


Publisher
Wiley-IEEE Press
Year
2023
Tongue
English
Leaves
291
Series
IEEE Press Series on Control Systems Theory and Applications
Category
Library

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✦ Synopsis


Control over Communication Networks

Advanced and systematic examination of the design and analysis of networked control systems and multi-agent systems

Control Over Communication Networks provides a systematic and nearly self-contained description of the analysis and design of networked control systems (NCSs) and multi-agent systems (MASs) over imperfect communication networks, with a primary focus on fading channels and delayed channels. The text characterizes the effect of communication channels on the stability and performance of NCSs, and further studies the joint impact of communication channels and network topology on the consensus of MASs.

By integrating communication and control theory, the four highly-qualified authors present fundamental results concerning the stabilization of NCSs over power-constrained fading channels and Gaussian finite-state Markov channels, linear-quadratic optimal control of NCSs with random input gains, optimal state estimation with intermittent observations, consensus of MASs with communication delay and packet dropouts, and synchronization of delayed Vicsek models.

Simulation results are given in each chapter to demonstrate the developed analysis and synthesis approaches. The references are comprehensive and up-to-date, enabling further study for readers.

Topics covered in Control Over Communication Networks include:

  • Basic foundational knowledge, including control theory, communication theory, and graph theory, to enable readers to understand more complex topics
  • The stabilization, optimal control, and remote state estimation problems of linear systems over channels with fading, signal-to-noise constraints, or intermittent measurements
  • Consensus problems of MASs over fading/delayed channels, with directed and undirected communication graphs

Control Over Communication Networks provides a valuable unified platform for understanding the analysis and design of NCSs and MASs for researchers, control engineers working on control systems over communication networks, and mechanical engineers working on unmanned systems. Preliminary knowledge of linear system theory and matrix analysis is required.

✦ Table of Contents


Cover
Title Page
Copyright
Contents
About the Authors
Preface
Acknowledgments
Acronyms
List of Symbols
Chapter 1 Introduction
1.1 Introduction and Motivation
1.1.1 Networked Control Systems
1.1.2 Multi‐Agent Systems
1.2 Literature Review
1.2.1 Basics of Communication Theory
1.2.2 Stabilization of NCSs
1.2.2.1 Control over Noiseless Digital Channels
1.2.2.2 Control over Stochastic Digital Channels
1.2.2.3 Control over Analog Channels
1.2.3 LQ Optimal Control of NCSs over Fading Channels
1.2.4 Estimation of NCSs with Intermittent Communication
1.2.4.1 Stability of Kalman Filtering with Intermittent Observations
1.2.4.2 Remote State Estimation with Sensor Scheduling
1.2.5 Distributed Consensus of MASs
1.3 Preview of the Book
1.4 Preliminaries
1.4.1 Graph Theory
1.4.2 Hadamard Product and Kronecker Product
Bibliography
Chapter 2 Stabilization over Power Constrained Fading Channels
2.1 Introduction
2.2 Problem Formulation
2.3 Fundamental Limitations
2.4 Mean‐Square Stabilizability
2.4.1 Scalar Systems
2.4.2 Two‐Dimensional Systems
2.4.2.1 Communication Structure
2.4.2.2 Encoder/Decoder Design
2.4.2.3 Scheduler Design
2.4.2.4 Scheduler Parameter Selection
2.4.2.5 Proof of Theorem 2.3
2.4.3 High‐Dimensional Systems: TDMA Scheduler
2.4.4 High‐Dimensional Systems: Adaptive TDMA Scheduler
2.4.4.1 Scheduling Algorithm
2.4.4.2 Scheduler Parameter Selection
2.4.4.3 Proof of Theorem 2.5
2.5 Numerical Illustrations
2.5.1 Scalar Systems
2.5.2 Vector Systems
2.6 Conclusions
Bibliography
Chapter 3 Stabilization over Gaussian Finite‐State Markov Channels
3.1 Introduction
3.2 Problem Formulation
3.2.1 Stability of Markov Jump Linear Systems
3.2.2 Sojourn Times for Markov Lossy Process
3.3 Fundamental Limitation
3.4 Stabilization over Finite‐State Markov Channels
3.4.1 Communication Structure
3.4.2 Observer/Estimator/Controller Design
3.4.3 Encoder/Decoder/Scheduler Design
3.4.4 Sufficient Stabilizability Conditions
3.5 Stabilization over Markov Lossy Channels
3.5.1 Two‐Dimensional Systems
3.5.1.1 Optimal Scheduler Design
3.5.1.2 Scheduler Parameter Selection
3.5.1.3 Sufficiency Proof of Theorem 3.4
3.5.2 High‐Dimensional Systems
3.5.3 Numerical Illustrations
3.6 Conclusions
Bibliography
Chapter 4 Linear‐Quadratic Optimal Control of NCSs with Random Input Gains
4.1 Introduction
4.2 Problem Formulation
4.3 Finite‐Horizon LQ Optimal Control
4.4 Solvability of Modified Algebraic Riccati Equation
4.4.1 Cone‐Invariant Operators
4.4.2 Solvability
4.5 LQ Optimal Control
4.6 Conclusion
Bibliography
Chapter 5 Multisensor Kalman Filtering with Intermittent Measurements
5.1 Introduction
5.2 Problem Formulation
5.3 Stability Analysis
5.3.1 Transmission Capacity
5.3.2 Preliminaries
5.3.3 Lower Bound
5.3.4 Upper Bound
5.3.5 Special Cases
5.4 Examples
5.5 Conclusions
Bibliography
Chapter 6 Remote State Estimation with Stochastic Event‐Triggered Sensor Schedule and Packet Drops
6.1 Introduction
6.2 Problem Formulation
6.3 Optimal Estimator
6.4 Suboptimal Estimators
6.4.1 Fixed Memory Estimator
6.4.2 Particle Filter
6.5 Simulations
6.6 Conclusions
Bibliography
Chapter 7 Distributed Consensus over Undirected Fading Networks
7.1 Introduction
7.2 Problem Formulation
7.3 Identical Fading Networks
7.4 Nonidentical Fading Networks
7.4.1 Definition of Edge Laplacian
7.4.2 Sufficient Consensus Conditions
7.5 Simulations
7.6 Conclusions
Bibliography
Chapter 8 Distributed Consensus over Directed Fading Networks
8.1 Introduction
8.2 Problem Formulation
8.3 Identical Fading Networks
8.3.1 Consensus Error Dynamics
8.3.2 Consensusability Results
8.3.3 Balanced Directed Graph Cases
8.4 Definitions and Properties of CIIM, CIM, and CEL
8.4.1 Definitions of CIIM, CIM, and CEL
8.4.2 Properties of CIIM, CIM, and CEL
8.5 Nonidentical Fading Networks
8.5.1 Λ=μI
8.5.1.1 Star Graphs
8.5.1.2 Directed Path Graphs
8.5.2 Λ≠μI
8.6 Simulations
8.7 Conclusions
Bibliography
Chapter 9 Distributed Consensus over Networks with Communication Delay and Packet Dropouts
9.1 Introduction
9.2 Problem Formulation
9.3 Consensusability with Delay and Identical Packet Dropouts
9.3.1 Stability Criterion of NCSs with Delay and Multiplicative Noise
9.3.2 Consensusability Conditions
9.4 Consensusability with Delay and Nonidentical Packet Dropouts
9.5 Illustrative Examples
9.6 Conclusions
Bibliography
Chapter 10 Distributed Consensus over Markovian Packet Loss Channels
10.1 Introduction
10.2 Problem Formulation
10.3 Identical Markovian Packet Loss
10.3.1 Analytic Consensus Conditions
10.3.2 Critical Consensus Condition for Scalar Agent Dynamics
10.4 Nonidentical Markovian Packet Loss
10.5 Numerical Simulations
10.6 Conclusions
Bibliography
Chapter 11 Synchronization of the Delayed Vicsek Model
11.1 Introduction
11.2 Directed Graphs
11.3 Problem Formulation
11.4 Synchronization of Delayed Linear Vicsek Model
11.5 Synchronization of Delayed Nonlinear Vicsek Model
11.6 Simulations
11.7 Conclusions
Bibliography
Index
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