Adaptive Sliding Mode Neural Network Control for Nonlinear Systems Emerging Methodologies and Applications in Modelling, Identification and Control Series
Auteurs : Li Yang, Zhang Jianhua, Qiong Wu
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
Jianhua Zhang. Associate professor in Hebei University of Science and Technology, Shijiazhuang, China. He obtained his BS degree from Jilin Normal University, China in 2003, his MS degree from Yanshan University, China in 2006 and his PhD from Yanshan University, China in 2011. His main research interests are in the areas of non-linear control systems, control systems design over network and intelligent control.
Mrs Wu obtained her BA and MA degrees from Hebei University of Science and Technology, China in 2010 and the University of Sheffield, England in 2011, respectively. Her main research interests are in the areas of Corpus Linguistics, Translation, and Language teaching.
- 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
Date de parution : 11-2018
Ouvrage de 186 p.
15x22.8 cm
Thème d’Adaptive Sliding Mode Neural Network Control for... :
Mots-clés :
Adaptive Control; Adaptive control; ADS-B; Backstepping control; Backstepping; Chaotic Sychronization; Exponential Stability Analysis; Feedback control; Intelligent flight; Lyapunov stability theory; Lyapunov Stability; Lyapunov theory; Multilateration; Neural networks applications; Neural networks; Nonlinear Systems Analysis; Nonlinear systems; Path planning; Robust Stability Analysis; Robust Stability; Sliding Mode Control; Sliding mode Control; Sliding mode control; Super-twisting Control; U