Networked control systems are increasingly ubiquitous today, with applications ranging from vehicle communication and adaptive power grids to space exploration and economics. The optimal design of such systems presents major challenges, requiring tools from various disciplines within applied mathematics such as decentralized control, stochastic control, information theory, and quantization. A thorough, self-contained book, Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints aims to connect these diverse disciplines with precision and rigor, while conveying design guidelines to controller architects. Unique in the literature, it lays a comprehensive theoretical foundation for the study of networked control systems, and introduces an array of concrete tools for work in the field.  Salient features included: ·         Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems.  ·         Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods.  ·         Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. ·         Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. ·         Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end. ·         Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems.  ·         Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods.  ·         Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. ·         Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. ·         Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.
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This book lays a comprehensive theoretical foundation for the study of networked control systems, and introduces tools for work in the field. Covers characterization, comparison and design of information structures in static and dynamic teams and much more.
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Introduction.- Part I Information Structures in Networked Control.- Networked Control Systems as Stochastic Team Decision Problems: A General Introduction.- Characterization and Comparison of Information Structures.- Topological Properties of Information Structures: Comparison, Convergence and Optimization.- Part II Stabilization of Networked Control Systems.- Coding for Control and Connections with Information Theory.- Stochastic Stability and Drift Criteria for Markov Chains in Networked Control.- Stochastic Stabilization over Noiseless Channels.- Stochastic Stabilization over Noisy Channels.- Stabilization of Decentralized Systems over Communication Channels.- Part III Optimization in Networked Control: Design of Optimal Policies under Information Constraints.- Optimization of Real-Time Coding and Control Policies: Structural and Existence Results.- Optimal Coding and Control for Linear Gaussian Systems over Gaussian Channels under Quadratic Cost.- Agreement in Teams and the Dynamic Programming Approach under Information Constraints.- A Topological Notions and Optimization.- B Probability Theory and Stochastic Processes.- C Markov Chains, Martingales and Ergodic Processes.- D Markov Decision Theory and Optimality of Markov Policies.- References.- Index.
Les mer
Networked control systems are increasingly ubiquitous today, with applications ranging from vehicle communication and adaptive power grids to space exploration and economics. The optimal design of such systems presents major challenges, requiring tools from various disciplines within applied mathematics such as decentralized control, stochastic control, information theory, and quantization. A thorough, self-contained book, Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints aims to connect these diverse disciplines with precision and rigor, while conveying design guidelines to controller architects. Unique in the literature, it lays a comprehensive theoretical foundation for the study of networked control systems, and introduces an array of concrete tools for work in the field.  Salient features include: ·         Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems.  ·         Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods.  ·         Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. ·         Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. ·         Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.
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From the reviews:“Explains the mathematics useful for the description of those systems, when imbedded in a mathematical framework of discrete time, and elements which take their values either in discrete or in Euclidean spaces … . The reviewer sees two uses for the book. It could be a valuable information source for someone interested in an overall picture of the subject … . other use would be for a reading course by a courageous student willing to reconstruct part of the material.” (A. F. Gualtierotti, Mathematical Reviews, March, 2014)
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The first book that covers information structures, stabilization and performance analysis in networked control systemsReports original research results, including the concept of random-time stochastic drift and recent developments in optimal quantizer design for centralized and decentralized systemsProvides fresh approaches to optimization of observation channels, and develops new notions of information structuresFigures, tables, references, glossary, and indexes enhance the presentation and accessibility of contentIncludes supplementary material: sn.pub/extras
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Produktdetaljer

ISBN
9781489992826
Publisert
2015-06-15
Utgiver
Vendor
Birkhauser Boston Inc
Vekt
7489 gr
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet