Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches.
This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering.
Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches.
This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering.
I. Introduction 1
II. Modeling and control of uncertain systems with friction 2
1. Friction dynamics and modeling
2. Adaptive control for servo systems with LuGrefriction model
3. Robust tracking control for two-inertia systems with friction
compensation
4. Adaptive prescribed performance control with continuous friction
model
5. Composite adaptive control with discontinuous piecewise
parametric friction model
III. Modeling and control of uncertain systems with input dead zone
6. Dead zone dynamics and modeling
7. Adaptive Robust Finite-Time Neural Control of Uncertain PMSM
Servo System with Nonlinear Dead Zone
8. Adaptive dynamic surface control for strict-feedback systems
with nonlinear dead zone
9. Adaptive prescribed performance control for strict-feedback
systems with nonlinear dead zone
10.A modified dynamic surface control for pure-feedback systems
with nonlinear dead zone
IV. Modeling and control of uncertain systems with saturation
11.Saturation dynamics and modeling
12.ESO based adaptive sliding mode control for systems with input
saturation
13.Nonsingular terminal sliding mode funnel control for systems
with unknown input saturation
14.Adaptive neural dynamic surface sliding mode control for
uncertain systems with saturation
V. Modeling and control of uncertain systems with hysteresis
15.Hysteresis dynamics and modeling
16.Adaptive parameter estimation and model inverse control for
uncertain systems with backlash
17.Parameter identification and control for Hammerstein systems
with hysteresis
18.Adaptive parameter estimation and suspension control with
continuous hysteresis model
Appendix A. Constants and Conversion Factors
Appendix B. Introduction to MATLAB
Jing Na received his B.Eng. and Ph.D. degrees from the School of Automation, Beijing Institute of Technology, Beijing, China, in 2004 and 2010, respectively. He was a Monaco/ITER Postdoctoral Fellow at the ITER Organization, Saint-Paul-lès-Durance, France, and also a Marie Curie Intra-European Fellow with the Department of Mechanical Engineering, University of Bristol, U.K. Since 2010, he has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China, where he became a professor in 2013. He has co-authored one monograph and more than 100 international journal and conference papers. His current research interests include intelligent control, adaptive parameter estimation, nonlinear control. Qiang Chen. Associate professor in the College of Information Engineering, Zhejiang University of Technology, Hangzhou, China. He received the B.S. degree in measurement and control technology and instrumentation from Hebei Agricultural University, Baoding, China, in 2006 and the Ph.D. degree in control science and engineering from Beijing Institute of Technology, Beijing, China, in 2012. His research interests include neural networks, sliding mode control and adaptive learning control with applications to motion control systems. Xuemei Ren received her B.S. degree from Shandong University, Shandong, China, in 1989, and M.S. and Ph.D. degrees in control engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1992 and 1995, respectively. She worked at the School of Automation, Beijing Institute of Technology as a professor from 2002. She has published more than 100 academic papers. Her research interests include nonlinear systems, intelligent control, neural network control, adaptive control, multi- drive servo systems and time delay systems.
"This book is interesting for both researchers and practitioners which can learn and understand nonlinear adaptive control designs. It is also useful for academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science. It may be used as a reference book on adaptive control for servo systems for students with some background in control engineering." --zbMATH
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