Data-driven iterative learning control for discrete-time systems / Ronghu Chi, Yu Hui, Zhongsheng Hou.
Chi, Ronghu.; Hui, Yu.; Hou, Zhongsheng.
2022
QA402.3
Available Online

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Title Data-driven iterative learning control for discrete-time systems / Ronghu Chi, Yu Hui, Zhongsheng Hou.
Author Chi, Ronghu.
ISBN 9789811959509 (electronic bk.)
9811959501 (electronic bk.)
9811959498
9789811959493
DOI https://doi.org/10.1007/978-981-19-5950-9
Publication Details Singapore : Springer, 2022.
Language English
Description 1 online resource (239 p.).
Item Number 10.1007/978-981-19-5950-9 doi
Call Number QA402.3
Dewey Decimal Classification 629.8/312
Summary This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the systems output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed November 30, 2022).
Added Author Hui, Yu.
Hou, Zhongsheng.
Series Intelligent control and learning systems ; v. 2.
Available in Other Form Data-Driven Iterative Learning Control for Discrete-Time Systems
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Chapter 1: Introduction
Chapter 2: Iterative Dynamic Linearization of Nonlinear Repetitive Systems
Chapter 3: Data-Driven Optimal Iterative Learning Control
Chapter 4: Knowledge Enhanced Data-Driven Optimal Terminal ILC
Chapter 5: Data-Driven Optimal Point-to-Point ILC using Intermidient Information
Chapter 6: Higher order Data-Driven Optimal Iterative Learning Control
Chapter 7: Data-Driven Optimal Iterative Learning Control with Varying Trial Length
Chapter 8: Data-Driven Optimal Iterative Learning Control with Package Dropouts
Chapter 9: Constrained Data-Driven Optimal Iterative Learning Control
Chapter 10: ESO-based Data-Driven Optimal Iterative Learning Control
Chapter 11: Quantized Data-Driven Optimal Iterative Learning Control
Chapter 12: Event-triggered Data-driven Optimal Iterative Learning Control
Chapter 13: Conclusions and Perspectives
Appendices.

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