Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics

by Jing Na, Qiang Chen PhD, Xuemei Ren

Overview

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. - Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics - Provides practical application and experimental results for robotic systems, and servo motors

Product Details

ISBN-13:	9780128136843
Publisher:	Elsevier Science & Technology Books
Publication date:	06/12/2018
Series:	Emerging Methodologies and Applications in Modelling, Identification and Control
Sold by:	Barnes & Noble
Format:	eBook
Pages:	336
File size:	22 MB
Note:	This product may take a few minutes to download.

About the Author

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 received his MSc degree in Measurement and Control Technology and Instrumentation from Hebei Agricultural University, Baoding, China, in 2006, and his PhD in Control Science and Engineering from the Beijing Institute of Technology, Beijing, China, in 2012. Since then, he has been with the School of Information Engineering at Zhejiang University of Technology, Hangzhou, China, where he is currently a Professor. His research interests include adaptive control and iterative learning control, with a focus on applications in 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.

Table of Contents

I. Introduction 1 II. Modeling and control of uncertain systems with friction 21. Friction dynamics and modeling2. Adaptive control for servo systems with LuGrefriction model 3. Robust tracking control for two-inertia systems with friction compensation4. Adaptive prescribed performance control with continuous friction model5. 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 saturation13.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 hysteresis18.Adaptive parameter estimation and suspension control with continuous hysteresis model Appendix A. Constants and Conversion Factors Appendix B. Introduction to MATLAB

What People are Saying About This

From the Publisher

Represents the first volume in the Emerging Methodologies and Applications in Modelling, Identification and Control series

Editorial Reviews

"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

From the Publisher