Discrete-Time Adaptive Iterative Learning Control
From Model-Based to Data-Driven
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Beschreibung
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.
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.
Focuses on discrete-time adaptive iterative learning control (DAILC) Proposes systematic procedures for design and analysis of model-based DAILC for parametric systems Proposes systematic procedures for design and analysis of adaptive terminal ILC for nonlinear systems
Autor*in
Ronghu Chi
Themen in »Discrete-Time Adaptive Iterative Learning Control«
Iterative Learning Control Adaptive Iterative Learning Control Terminal Iterative Learning Control Discrete-Time Systems Linear Parameterized Systems Nonlinear Parameterized Systems Nonlinear Affine Systems Nonlinear and Non-affine Systems SISO Systems MIMO Systems System Uncertainties
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“This book should be viewed as a (relatively) small handbook of discrete-time adaptive iterative learning control (DAILC) in its (very) contemporary version. … The book can serve both as a handbook but also a textbook for graduate and postgraduate researchers.” (Vladimir Răsvan, zbMATH 1491.93002, 2022)
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