[1]LI Dong-sheng,SHAO Shan,CHEN Jun,et al.Design and stability analysis of a fuzzy controller with uncertain degrees of membership[J].CAAI Transactions on Intelligent Systems,2010,5(1):17-23.
Copy

Design and stability analysis of a fuzzy controller with uncertain degrees of membership

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 1 Page number: 17-23 Column: 学术论文—人工智能基础 Public date: 2010-02-25
Title:
Design and stability analysis of a fuzzy controller with uncertain degrees of membership
Author(s):
LI Dong-sheng1;  SHAO Shan2;  CHEN Jun1;  WEI Chen1;  DUAN Hai-bin1;  ZOU Jie3
1.National Key Laboratory of Science and Technology on Holistic Flight Control, Beihang University, Beijing 100191, China;
2.Department of Flight Control, Shenyang Aircraft Design and Research Institute, Shenyang 110035, China;
3.Key Laboratory of National Defense Science and Technology on Fire Control Technology, Luoyang Institute of ElectroOptical Equipment, Luoyang 471009, China
Keywords:
TakagiSugeno(T-S) fuzzy model;  fuzzy controller;  membership function;  linear matrix inequality(LMI);  uncertain grades of membership
CLC:
TP273.4
DOI:
-
Abstract:
Many nonlinear systems are so uncertain that they are difficult to be described accurately with mathematical models. Following an analysis of the basic TakagiSugeno (TS) fuzzy model, by adding a free variable in the membership function, we were able to design a state feedback controller using linear matrix inequalities (LMI). The controller made the closedloop system tend to an asymptotic stability. Stable conditions made full use of relationships between constructive information about prior states and the consequences of actions in local subsystems. The proposed method reduced the complexity of descriptions of the conditions leading to stability in conventional TS fuzzy models and also reduced complexity when solving related problems. Experimental results indicated that the proposed approach is feasible and effective.
References:
［1］TAKAGI T, SUGENO M. Fuzzy identification of systems and its applications to modeling and control［J］. IEEE Transactions on Systems, Man, and CyberneticsPart B: Cybernetics, 1985, 15(1): 116132.
［2］SUGENO M, KANG G T. Structure identification of fuzzy model［J］. Fuzzy Sets and Systems, 1988, 28: 1533.
［3］TANAKA K, IKEDE T, WANG H O. Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMIbased design［J］. IEEE Transactions on Fuzzy Systems, 1998, 6: 250265.
［4］KIM E, LEE H. New approaches to relaxed quadratic stability condition of fuzzy control systems［J］. IEEE Transactions on Fuzzy Systems, 2000, 8(5): 523534.
［5］FANG C, LIU Y, KAU S, et al. A new LMIbased approach to relaxed quadratic stabilization of TS fuzzy control systems［J］. IEEE Transactions on Fuzzy Systems, 2006, 14(3): 386397.
［6］SALA A, ARINO C. Relaxed stability and performance conditions for TakagiSugeno fuzzy system with knowledge on membership function overlap［J］. IEEE Transactions on Systems, Man, and CyberneticsPart B: Cybernetics, 2007, 37(3): 727732.
［7］CHEN Zhaona, LIU Bin, JING Yuanwei. Robust stabilization for TS fuzzy control systems with parametric uncertainties via LMI approach［C］//Proceedings of Chinese Control and Decision Conference. Yantai, China, 2008: 33983402.
［8］LAM H K, LEUNG F H F. Stability analysis of fuzzy control systems subject to uncertain grades of membership［J］. IEEE Transactions on Systems, Man, and CyberneticsPart B: Cybernetics, 2005, 35(6): 13221325.
［9］CARLOS A, ANTONIO S. Extensions to “stability analysis of fuzzy control systems subject to uncertain grades of membership”［J］. IEEE Transactions on Systems, Man, and CyberneticsPart B: Cybernetics, 2008, 38(2): 558563.
［10］LIU X, ZHANG Q. New approaches to control designs based on fuzzy observers for TS fuzzy systems via LMI［J］. Automatica, 2003, 39: 15711582.
Similar References:

Memo

-

Last Update: 2010-03-31

Copyright © CAAI Transactions on Intelligent Systems