Muutke küpsiste eelistusi

Networked Control Systems with Intermittent Feedback [Kõva köide]

(University of Dubrovnik, Dubrovnik, Croatia), (Technical University of Munich, Germany)
  • Formaat: Hardback, 258 pages, kõrgus x laius: 234x156 mm, kaal: 612 g, 6 Tables, black and white; 22 Line drawings, color; 7 Line drawings, black and white; 10 Halftones, color
  • Sari: Automation and Control Engineering
  • Ilmumisaeg: 10-Apr-2017
  • Kirjastus: CRC Press Inc
  • ISBN-10: 1498756344
  • ISBN-13: 9781498756341
Teised raamatud teemal:
Networked Control Systems with Intermittent FeedbackSuurem pilt
  • Formaat: Hardback, 258 pages, kõrgus x laius: 234x156 mm, kaal: 612 g, 6 Tables, black and white; 22 Line drawings, color; 7 Line drawings, black and white; 10 Halftones, color
  • Sari: Automation and Control Engineering
  • Ilmumisaeg: 10-Apr-2017
  • Kirjastus: CRC Press Inc
  • ISBN-10: 1498756344
  • ISBN-13: 9781498756341
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781498756341.html
Märksõnad:
Networked Control Systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators and controllers is realized by a shared (wired or wireless) communication network. NCSs offer several advantages, such as reduced installation and maintenance costs, as well as greater flexibility, over conventional control systems in which parts of control loops exchange information via dedicated point-to-point connections. The principal goal of this book is to present a coherent and versatile framework applicable to various settings investigated by the authors over the last several years. This framework is applicable to nonlinear time-varying dynamic plants and controllers with delayed dynamics; a large class of static, dynamic, probabilistic and priority-oriented scheduling protocols; delayed, noisy, lossy and intermittent information exchange; decentralized control problems of heterogeneous agents with time-varying directed (not necessarily balanced) communication topologies; state- and output-feedback; off-line and on-line intermittent feedback; optimal intermittent feedback through Approximate Dynamic Programming (ADP) and Reinforcement Learning (RL); and control systems with exogenous disturbances and modeling uncertainties.
Preface xiii
List of Figures
xvii
List of Tables
xxi
Contributors xxiii
Symbols and Abbreviations xxv
1 Introduction
1(12)
1.1 Why Study Intermittent Feedback?
5(3)
1.2 Historical Aspects and Related Notions
8(1)
1.3 Open Problems and Perspectives
9(1)
1.4 Notation
10(3)
I PLANT-CONTROLLER APPLICATIONS
13(130)
2 MATIs with Time-Varying Delays and Model-Based Estimators
15(36)
2.1 Motivation, Applications and Related Works
16(1)
2.2 Impulsive Delayed Systems and Related Stability Notions
17(1)
2.3 Problem Statement: Stabilizing Transmission Intervals and Delays
18(4)
2.4 Computing Maximally Allowable Transfer Intervals
22(5)
2.4.1 £P-Stability with Bias of Impulsive Delayed LTI Systems
23(2)
2.4.2 Obtaining MATIs via the Small-Gain Theorem
25(2)
2.5 Numerical Examples: Batch Reactor, Planar System and Inverted Pendulum
27(13)
2.5.1 Batch Reactor with Constant Delays
27(4)
2.5.2 Planar System with Constant Delays
31(4)
2.5.3 Inverted Pendulum with Time-Varying Delays
35(5)
2.6 Conclusions and Perspectives
40(1)
2.7 Proofs of Main Results
40(11)
2.7.1 Proof of Lemma 2.1
40(4)
2.7.2 Proof of Theorem 2.1
44(2)
2.7.3 Proof of Theorem 2.2
46(2)
2.7.4 Proof of Corollary 2.1
48(1)
2.7.5 Proof of Proposition 2.1
48(3)
3 Input-Output Triggering
51(34)
3.1 Motivation, Applications and Related Works
52(5)
3.1.1 Motivational Example: Autonomous Cruise Control
52(2)
3.1.2 Applications and Literature Review
54(3)
3.2 Impulsive Switched Systems and Related Stability Notions
57(3)
3.3 Problem Statement: Self-Triggering from Input and Output Measurements
60(2)
3.4 Input-Output Triggered Mechanism
62(8)
3.4.1 Why £-gains over a Finite Horizon?
63(1)
3.4.2 Proposed Approach
64(1)
3.4.3 Design of Input-Output Triggering
65(1)
3.4.3.1 Cases 3.1 and 3.2
66(2)
3.4.3.2 Case 3.3
68(1)
3.4.4 Implementation of Input-Output Triggering
68(2)
3.5 Example: Autonomous Cruise Control
70(3)
3.6 Conclusions and Perspectives
73(3)
3.7 Proofs of Main Results
76(9)
3.7.1 Properties of Matrix Functions
76(1)
3.7.2 Proof of Theorem 3.1
77(1)
3.7.3 Proof of Theorem 3.2
78(2)
3.7.4 Proof of Results in Section 3.4.3
80(1)
3.7.4.1 Cp property over an arbitrary finite interval with constant 6
80(1)
3.7.4.2 Extending bounds to (an arbitrarily long) finite horizon
81(1)
3.7.4.3 Proof of Theorem 3.3
82(1)
3.7.4.4 Proof of Theorem 3.4
82(3)
4 Optimal Self-Triggering
85(14)
4.1 Motivation, Applications and Related Works
85(2)
4.2 Problem Statement: Performance Index Minimization
87(2)
4.3 Obtaining Optimal Transmission Intervals
89(5)
4.3.1 Input-Output-Triggering via the Small-Gain Theorem
89(1)
4.3.2 Dynamic Programming
90(1)
4.3.3 Approximate Dynamic Programming
91(1)
4.3.4 Approximation Architecture
91(1)
4.3.4.1 Desired Properties
92(1)
4.3.5 Partially Observable States
93(1)
4.4 Example: Autonomous Cruise Control (Revisited)
94(1)
4.5 Conclusions and Perspectives
95(4)
5 Multi-Loop NCSs over a Shared Communication Channels
99(44)
5.1 Motivation, Applications and Related Works
100(4)
5.1.1 Medium Access Control
101(3)
5.2 Markov Chains and Stochastic Stability
104(3)
5.2.1 Markov Chains
104(1)
5.2.2 Stochastic Stability
105(2)
5.3 Problem Statement: Scheduling in Multi-Loop NCS
107(2)
5.4 Stability and Performance
109(8)
5.4.1 Event-Based Scheduling Design
109(3)
5.4.2 Stability Analysis
112(2)
5.4.3 Performance and Design Guidelines
114(2)
5.4.4 Scheduling in the Presence of Channel Imperfections
116(1)
5.5 Decentralized Scheduler Implementation
117(4)
5.6 Empirical Performance Evaluation
121(5)
5.6.1 Optimized Thresholds A for the λ-Character Scheduler
121(1)
5.6.2 Comparison for Different Scheduling Policies
122(1)
5.6.3 Performance of the Decentralized Scheduler
123(2)
5.6.4 Performance with Packet Dropouts
125(1)
5.7 Conclusions and Perspectives
126(1)
5.8 Proofs and Derivations of Main Results
127(16)
5.8.1 Proof of Theorem 5.3
127(3)
5.8.2 Proof of Corollary 5.1
130(1)
5.8.3 Proof of Theorem 5.4
131(1)
5.8.4 Proof of Proposition 5.2
132(3)
5.8.5 Proof of Proposition 5.3
135(8)
II MULTI-AGENT APPLICATIONS
143(70)
6 Topology-Triggering of Multi-Agent Systems
145(32)
6.1 Motivation, Applications and Related Works
146(3)
6.2 Initial-Condition-(In)dependent Multi-Agent Systems and Switched Systems
149(2)
6.2.1 Switched Systems and Average Dwell Time
150(1)
6.2.2 Graph Theory
151(1)
6.3 Problem Statement: Transmission Intervals Adapting to Underlying Communication Topologies
151(2)
6.4 Topology-Triggering and Related Performance vs. Lifetime Trade-Offs
153(8)
6.4.1 Designing Broadcasting Instants
154(4)
6.4.2 Switching Communication Topologies
158(1)
6.4.2.1 Switching without Disturbances
158(2)
6.4.2.2 Switching with Disturbances
160(1)
6.5 Example: Output Synchronization and Consensus Control with Experimental Validation
161(7)
6.5.1 Performance vs. Lifetime Trade-Offs
163(1)
6.5.2 Experimental Setup
164(2)
6.5.3 Energy Consumption
166(1)
6.5.4 Experimental Results
167(1)
6.6 Conclusions and Perspectives
168(2)
6.7 Proofs and Derivations of Main Results
170(7)
6.7.1 From Agent Dynamics to Closed-Loop Dynamics
170(1)
6.7.2 Introducing Intermittent Data Exchange
171(1)
6.7.3 Proof of Proposition 6.1
172(1)
6.7.4 Proof of Theorem 6.2
172(2)
6.7.5 Proof of Theorem 6.3
174(1)
6.7.6 Proof of Theorem 6.4
175(2)
7 Cooperative Control in Degraded Communication Environments
177(20)
7.1 Motivation, Applications and Related Works
178(1)
7.2 Impulsive Delayed Systems
179(1)
7.3 Problem Statement: Stabilizing Transmission Intervals and Delays
180(2)
7.4 Computing Maximally Allowable Transfer Intervals
182(3)
7.4.1 Interconnecting the Nominal and Error System
183(1)
7.4.2 MASs with Nontrivial Sets B
183(1)
7.4.3 Computing Transmission Intervals τ
184(1)
7.5 Example: Consensus Control with Experimental Validation
185(5)
7.6 Conclusions and Perspectives
190(3)
7.7 Proofs of Main Results
193(4)
7.7.1 Proof of Theorem 7.1
193(1)
7.7.2 Proof of Corollary 7.1
194(3)
8 Optimal Intermittent Feedback via Least Square Policy Iteration
197(16)
8.1 Motivation, Applications and Related Works
198(1)
8.2 Problem Statement: Cost-Minimizing Transmission Policies
199(2)
8.3 Computing Maximally Allowable Transfer Intervals
201(7)
8.3.1 Stabilizing Interbroadcasting Intervals
201(3)
8.3.2 (Sub)optimal Interbroadcasting Intervals
204(4)
8.4 Example: Consensus Control (Revisited)
208(1)
8.5 Conclusions and Perspectives
209(4)
Bibliography 213(18)
Index 231
Dr. Domagoj Toli graduated from the Faculty of Electrical Engineering and Computing (FER), University of Zagreb, with a Master degree (Dipl.-Ing.) in Electrical Engineering (2007), majoring in Control Systems. In addition, he graduated from the Mathematics Department, University of Zagreb, with a Bachelor Degree in Mathematics (2008). Subsequently, he enrolled in the Ph.D. program, the Control Systems major, at the Department of Electrical and Computer Engineering, University of New Mexico (UNM), Albuquerque, NM, as a member of the MARHES (Multi-Agent, Robotics, Hybrid, and embedded Systems Laboratory) research group under supervision of Prof. Rafael Fierro. Upon completing the Ph.D. program (2012), he was a postdoctoral researcher in the Research Centre for Advanced Cooperative Systems (ACROSS) at FER until September 2014. During his time in ACROSS, Dr. Toli was a visiting researcher at the Institute for Information-oriented Control, Technische Universität München from October 2013 until June 2014. Currently, he is a postdoctoral researcher at University of Dubrovnik. His research focuses on stability and estimation under intermittent information for nonlinear and multi-agent control systems. The developed theory is applied to problems in the area of multi-agent robotics.

Professor Sandra Hirche holds the TUM Liesel Beckmann Distinguished Professorship and heads the Chair of Information-oriented Control in the Department of Electrical and Computer Engineering at Technische Universität München, Germany (since 2013). She received the engineering degree in Aeronautical and Aerospace Engineering in 2002 from the Technical University Berlin, Germany, and the Doctor of Engineering degree in Electrical and Computer Engineering in 2005 from the Technische Universität München, Munich, Germany. From 2005-2007, she was a Post-Doctoral fellow of the Japanese Society for the Promotion of Science at the Fujita Laboratory at Tokyo Institute of Technology, Japan. Prior to her present appointment she has been an Associate Professor at Technische Universität München. Her main research interests include cooperative, distributed, and networked control with applications in human-robot interaction, multi-robot systems, and general robotics. She has published more than 150 papers in international journals, books, and refereed conferences. Dr. Hirche has received multiple awards such as the Rohde & Schwarz Award for her PhD thesis in 2005, the JSPS Postdoctoral Fellowship Award in 2005, the IFAC World Congress Best Poster Award in 2005, Best Paper Awards of IEEE Worldhaptics, and IFAC Conference of Maneuvering and Control of Marine Craft in 2009. Additionally, she was a finalist in the 2011 Ro-Man, the 2012 IROS Best Paper Awards, and the 2014 ECC Best Student Paper Awards. In 2013, she was awarded an ERC Starting Grant on the "Control based on Human Models."