Data-Driven Iterative Learning Control for Discrete-Time Systems

Language: English

Published by Springer, 2022

9811959498 / 9789811959493

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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 system's 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. Sprache: Englisch Gewicht in Gramm: 534. …

Title
Data-Driven Iterative Learning Control for Discrete-Time Systems
Author
Zhongsheng Hou, Yu Hui, Ronghu Chi
Publisher
Springer
Publication year
2022
Condition
Neu
Binding
Gebundene Ausgabe
Language
English
ISBN 10
9811959498
ISBN 13
9789811959493
Item weight
534 grams

Home-set

Mannheim, Germany

5-star seller

AbeBooks seller since April 13, 2026

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