T2: Model based Fuzzy Logic Control: Overview and Perspectives

Description

Fuzzy logic control was originally introduced and developed as a model free control design approach. However it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research effort on fuzzy logic control have been devoted to model based fuzzy control systems that guarantee not only stability but also performance of closed loop fuzzy control systems. This talk presents a survey on recent developments of analysis and design of model based fuzzy control systems. Attention will be focused on the so-called Takagi-Sugeno fuzzy models, their universal function approximation property and representation theory, stability analysis and controller design. Perspectives of model based fuzzy control in future are also discussed.

The topics of the tutorial include:

• BRIEF REVIEW OF FUZZY LOGIC CONTROL
• T–S FUZZY MODEL AND UNIVERSAL FUNCTION APPROXIMATION
• REPRESENTATION THEORY OF T-S FUZZY MODELS
• STABILITY ANALYSIS BASED ON COMMON AND PIECEWISE QUADRATIC LYAPUNOV FUNCTIONS
• STABILIZATION BASED ON COMMON QUADRATIC LYAPUNOV FUNCTIONS
• STABILIZATION BASED ON PIECEWISE QUADRATIC LYAPUNOV FUNCTIONS
• STABILIZATION BASED ON FUZZY LYAPUNOV FUNCTIONS
• FUTURE PERSPECTIVES

About the presenters

Gang Feng received the B.Eng and M.Eng. degrees in Automatic Control (of Electrical Engineering) from Nanjing Aeronautical Institute, China in 1982 and 1984 respectively, and the Ph.D. degree in Electrical Engineering from the University of Melbourne, Australia in 1992. He has been with City University of Hong Kong since 2000, where he is currently a professor, and was with School of Electrical Engineering, University of New South Wales, Australia, 1992-1999. He was awarded an Alexander von Humboldt Fellowship in 1997-1998. He was a visiting Fellow at National University of Singapore (1997), and Aachen Technology University, Germany (1997-1998). He has authored or co-authored over 130 international journal papers including 40 plus in IEEE Transactions. His current research interests include robust adaptive control, hybrid systems, and intelligent systems and control. Prof. Feng is an associate editor of IEEE Trans. on Automatic Control, IEEE Trans. on Fuzzy Systems, and IEEE Trans. on Systems, Man & Cybernetics, Part C, Journal of Control Theory and Applications, and was an associate editor of the Conference Editorial Board of IEEE Control System Society.

Xiao-Jun Zeng received the B.Sc. degree in mathematics in 1982 and the M.Sc. degree in Control Theory and Operation Research respectively from Xiamen University, Xiamen, China, in 1985, and the Ph.D. degree in computation from the University of Manchester, Manchester, U.K., in 1996. He has been with the University of Manchester since 2002 and is currently a Senior Lecturer in the School of Computer Science. From 1996 to 2002, he was with Knowledge Support Systems (KSS) Ltd., Manchester, where he was a Scientific Developer, Senior Scientific Developer, and Head of Research, developing intelligent decision support systems which won the European IST Award in 1999 and Microsoft European Retail Application Developer (RAD) Awards in 2001 and 2003. From 1985 to 1992, he was with the Department of Computer and Systems Sciences, Xiamen University, where he was a Lecturer and an Associate Professor. He has published more than 50 journal and conference papers including 10 IEEE Transaction papers. His current research interests include fuzzy control and systems, neural networks, decision support systems, intelligent systems, and data mining. Dr. Zeng is an Associate Editor of the IEEE Trans. on Fuzzy Systems and is a member of the editorial board of the International Journal of Computational Intelligence Research.