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

Discrete-time adaptive iterative learning control (DAILC) is a cutting-edge of ILC that can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book discusses the design and analysis of model-based DAILC methods, as well as data-driven DAILC methods, to facilitate broader applications. It is intended for academic scholars, engineers, and graduate students interested in learning control, adaptive control, nonlinear systems, and related fields.

Format: Hardback
Length: 206 pages
Publication date: 22 March 2022
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the realm of control and systems theory, focusing on the cutting-edge topic of discrete-time adaptive iterative learning control (DAILC). DAILC emerges as a powerful tool to address various challenges in practical applications, including dealing with random initial states, iteration-varying targets, and non-repetitive uncertainties.

The book begins by introducing the design and analysis of model-based DAILC methods, drawing upon the tools developed in discrete-time adaptive control theory. Recognizing the complexities inherent in modeling complex systems, the book then explores data-driven DAILC approaches, which establish a linear parametric data mapping between consecutive iterations. This innovative method facilitates the representation and manipulation of complex systems, enabling more accurate and efficient control.

Furthermore, the book delves into other significant improvements and extensions of model-based/data-driven DAILC, broadening its applications across diverse fields. It discusses advanced topics such as model predictive control, adaptive neuro-fuzzy inference systems, and robust control, providing readers with a comprehensive understanding of the latest developments in DAILC.

The book is meticulously crafted to cater to academic scholars, engineers, and graduate students interested in exploring control, adaptive control, nonlinear systems, and related disciplines. It offers a comprehensive and up-to-date overview of DAILC, presenting theoretical foundations, practical implementations, and real-world case studies. With its clear explanations, illustrative examples, and extensive references, this book serves as a valuable resource for anyone seeking to advance their knowledge and expertise in this dynamic field.

Weight: 494g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811904639
Edition number: 1st ed. 2022