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

  • 1st Edition - June 12, 2018
  • Latest edition
  • Authors: Jing Na, Qiang Chen, Xuemei Ren
  • Language: English

Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems w… Read more

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Description

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.

Key features

  • 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

Readership

Researchers and engineers working on the topics of electrical engineering, process engineering, computer science, mechanical engineering, automotive and aerospace, engineering and the other manmade systems

Table of contents

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 controlfor 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 Hammersteinsystems with hysteresis

18.Adaptive parameter estimation and suspension control with continuous hysteresis model

Appendix A. Constants and Conversion Factors
Appendix B. Introduction to MATLAB

Review quotes

"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

Product details

  • Edition: 1
  • Latest edition
  • Published: June 20, 2018
  • Language: English

About the authors

JN

Jing Na

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.
Affiliations and expertise
Professor, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China

QC

Qiang Chen

Qiang Chen received the B.S. degree in measure 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. Since 2012, he has been with the College of Information Engineering, Zhejiang University of Technology, Hangzhou, China, where he was a Professor in 2022. He has published over 100 peer-reviewed papers in journals and conference proceedings. He has been authorized more than 60 invention patents, 13 of which were transferred. His research interests include adaptive control and iterative learning control with application to motion control systems.

Affiliations and expertise
Professor, Deputy Dean of the Graduate School, and Director of the Provincial Experimental Teaching Center for Electronic Information, School of Information Engineering, Zhejiang University of Technology, Xihu District, Hangzhou, Zhejiang, China

XR

Xuemei Ren

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.
Affiliations and expertise
Professor, School of Automation, Beijing Institute of Technology, Beijing, China

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