Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

Discusses the fundamental aspects of nonlinear control theory, from basic concepts, to controller design methods

Yang Li (Author), Jianhua Zhang (Author), Wu Qiong (Author)

9780128153727, Elsevier Science

Paperback, published 21 November 2018

186 pages
22.9 x 15.1 x 1.3 cm, 0.29 kg

"The book is well organized and presents the most important adaptive sliding mode neural network control method for nonlinear systems. Suitable for senior undergraduate and graduate students as well as practical engineers, scientists and researchers interested in adaptive sliding mode neural network control for nonlinear system." --zbMATH

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering.

1. Basic Concepts 2. Nonlinear Systems Analysis Approach 3. Classical Nonlinear Systems Control 4. Advanced Nonlinear Systems Controller Design 5. Intelligent Methodology 6. Applications

Subject Areas: Mechanical engineering [TGB]