Yang Li, Jianhua Zhang, Wu Qiong

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

• Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields
• Offers instructive examples and simulations, including source codes
• Provides the basic architecture of control science and engineering

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 186
• Erscheinungstermin: 16. November 2018
• Englisch
• ISBN-13: 9780128154328
• Artikelnr.: 52016617

Autorenporträt

Yang Li. Lecturer at the Institute of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, China. She obtained her PhD from Yanshan University, China in 2014. She was a visiting student of the University of the West of England in 2012. Her main research interests are in the areas of sliding mode control, neural network control, time delay system and control applications.

Inhaltsangabe

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

Rezensionen

"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