Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

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Synopsis

The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems. 

Book details

Edition:
1st ed. 2022
Author:
Kasra Esfandiari, Farzaneh Abdollahi, Heidar A. Talebi
ISBN:
9783030731366
Related ISBNs:
9783030731359
Publisher:
Springer International Publishing
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2021-07-19
Usage restrictions:
Copyright
Copyright date:
2022
Copyright by:
Springer Nature Switzerland AG 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Mathematics and Statistics, Nonfiction, Technology