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Iterative Learning Control Over Random Fading Channels

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Iterative Learning Control Over Random Fading Channels

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Author : Dong Shen
language : en
Publisher: CRC Press
Release Date : 2023-12-22

Iterative Learning Control Over Random Fading Channels written by Dong Shen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-22 with Computers categories.

Random fading communication is a type of attenuation damage of data over certain propagation media. Establishing a systematic framework for the design and analysis of learning control schemes, the book studies in depth the iterative learning control for stochastic systems with random fading communication. The authors introduce both cases where the statistics of the random fading channels are known in advance and unknown. They then extend the framework to other systems, including multi-agent systems, point-to-point tracking systems, and multi-sensor systems. More importantly, a learning control scheme is established to solve the multi-objective tracking problem with faded measurements, which can help practical applications of learning control for high-precision tracking of networked systems. The book will be of interest to researchers and engineers interested in learning control, data-driven control, and networked control systems.

Iterative Learning Control Over Random Fading Channels

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Author : Dong Shen
language : en
Publisher: CRC Press
Release Date : 2023-12-22

Iterative Learning Control With Passive Incomplete Information

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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2018-04-16

Iterative Learning Control With Passive Incomplete Information written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-16 with Technology & Engineering categories.

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.

Iterative Learning Control

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Author : Hyo-Sung Ahn
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-28

Iterative Learning Control written by Hyo-Sung Ahn and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-28 with Technology & Engineering categories.

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

Iterative Learning Control With Passive Incomplete Information

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Author : Dong Shen
language : en
Publisher:
Release Date : 2018

Iterative Learning Control With Passive Incomplete Information written by Dong Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Intelligent control systems categories.

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.

Iterative Learning Control For Systems With Iteration Varying Trial Lengths

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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2019-01-29

Iterative Learning Control For Systems With Iteration Varying Trial Lengths written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Technology & Engineering categories.

This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerous intuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.

Discrete Time Adaptive Iterative Learning Control

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Author : Ronghu Chi
language : en
Publisher: Springer
Release Date : 2023-03-23

Discrete Time Adaptive Iterative Learning Control written by Ronghu Chi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-23 with Technology & Engineering categories.

This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.