Iterative Learning Control with Passive Incomplete Information: Algorithms Design and Convergence Analysis - Softcover

Shen, Dong

9789811341052: Iterative Learning Control with Passive Incomplete Information: Algorithms Design and Convergence Analysis

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ISBN 10: 9811341052 ISBN 13: 9789811341052

Verlag: Springer, 2018

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VerlagSpringer
Erscheinungsdatum2018
ISBN 10 9811341052
ISBN 13 9789811341052
EinbandTapa blanda
SpracheEnglisch
Anzahl der Seiten308

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Iterative Learning Control with Passive Incomplete Information: Algorithms Design and Convergence Analysis

Dong Shen

Verlag: Springer Singapore, 2018

ISBN 10: 9811341052 ISBN 13: 9789811341052

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a comprehensive discussion of iterative learning control (ILC) in various data dropout environments Proposes several systematic procedures for the design and analysis of ILC for stochastic systems with passive incomplete information . Bestandsnummer des Verk�ufers 266008199

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Iterative Learning Control with Passive Incomplete Information

Dong Shen

Verlag: Springer Nature Singapore Dez 2018, 2018

ISBN 10: 9811341052 ISBN 13: 9789811341052

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.-a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model-for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields. 308 pp. Englisch. Bestandsnummer des Verk�ufers 9789811341052

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Iterative Learning Control with Passive Incomplete Information : Algorithms Design and Convergence Analysis

Dong Shen

Verlag: Springer Nature Singapore, Springer Nature Singapore, 2018

ISBN 10: 9811341052 ISBN 13: 9789811341052

Neu Taschenbuch

Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.-a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model-for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields. Bestandsnummer des Verk�ufers 9789811341052

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