Discrete-Time Adaptive Iterative Learning Control: From Model-Based to Data-Driven

Discrete-Time Adaptive Iterative Learning Control: From Model-Based to Data-Driven (Intelligent Control and Learning Systems, 1) 1st ed. 2022 Edition
Author: Ronghu Chi (Author), Na Lin (Author), Huimin Zhang (Author), Ruikun Zhang (Author)
Publisher Finelybook 出版社:Springer; 1st ed. 2022 edition (March 22, 2022)
Language 语言:English
pages 页数:216 pages
ISBN-10 书号:9811904634
ISBN-13 书号:9789811904639

Book Description
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 Author: 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 Author: 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.

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