Intelligent Adaptive Control with System Constraints: Evolving Neural Network Approaches for Robust Adaptive Control

This book provides a comprehensive overview of Adaptive control system design, with a particular emphasis on the recent advancements, covering important practical aspects such as quick adaptation without high transients, adaptation within applicable constraints on system states and control, and model-free adaptive control with smart neural networks. Standard topics in adaptive control and important introductory materials on topics such as Nonlinear system stability using Lyapunov theory are also included in this book. This book provides a clear understanding and an expedited learning experience of both fundamental and advanced topics in Intelligent Adaptive Control to students, faculty, control scientists, and practising engineers interested in designing useful Adaptive control solutions for challenging practical problems. Numerous illustrative problems are included in this book to facilitate a better understanding of the concepts presented. This book is a useful guide for those interested in advanced and evolving topics in adaptive control.