Discrete-time adaptive iterative learning control : from model-based to data-driven / Ronghu Chi, Na Lin, Huimin Zhang, Ruikun Zhang.
Chi, Ronghu, author.; Lin, Na, author.; Zhang, Huimin, author.; Zhang, Ruikun, author.
2022
QA402.3 .C55 2022
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Title
Discrete-time adaptive iterative learning control : from model-based to data-driven / Ronghu Chi, Na Lin, Huimin Zhang, Ruikun Zhang.
Author
Chi, Ronghu, author.
ISBN
9789811904646 (electronic bk.)
9811904642 (electronic bk.)
9789811904639
9811904634
DOI
https://doi.org/10.1007/978-981-19-0464-6
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (chiefly color).
Item Number
10.1007/978-981-19-0464-6 doi
Call Number
QA402.3 .C55 2022
Dewey Decimal Classification
629.8/312
Summary
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.
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 April 5, 2022).
Added Author
Lin, Na, author.
Zhang, Huimin, author.
Zhang, Ruikun, author.
Series
Intelligent control and learning systems ; volume 1. 2662-5466
Available in Other Form
Print version: 9789811904639
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Chapter 1: Introduction
Part 1: Model-based Discrete-time Adaptive ILC
Chapter 2: Discrete-time Adaptive ILC for Linear Parametric Systems
Chapter 3: Discrete-time Adaptive ILC for Higher order Parametric Systems
Chapter 4: Data-weighted Discrete-time Adaptive ILC Chapter
5: Discrete-time Adaptive ILC for Nonparametric Nonlinear Systems Part 2: Data-driven Discrete-time Adaptive ILC Chapter
6: Neural Network based Discrete-time Adaptive ILC
Chapter 7: Data-driven Discrete-time Adaptive ILC for Nonaffined Nonlinear Systems
Chapter 8: Multi-input Enhanced Data-driven Discrete-time Adaptive ILC
Chapter 9: High-order Internal Model based Data-driven Terminal Adaptive ILC
Chapter 10: Conclusions Appendices.

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