An LMI-based stable T-S fuzzy model with parametric uncertainties using multiple Lyapunov function approach

被引：0
|
作者：
Liu, CH
Hwang, HD
Tsai, ZR
Twu, SH
机构：
[1] Chung Yuan Christian Univ, Dept Elect Engn, Taoyuan 320, Taiwan
[2] Jin Wen Inst Technol, Dept Elect Engn, Taipei 231, Taiwan
[3] Chang Gung Univ, Dept Elect Engn, Kwei San Shian 333, Taiwan
[4] Chung Yuan Christian Univ, Dept Elect Engn, Taoyuan 320, Taiwan
来源：
2004 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2 | 2004年
关键词：
Fuzzy Lyapunov function; linear matrix inequality; parametric uncertainties; parallel distributed compensation; Chaotic Lorenz system;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper addresses stability analysis and stabilization for Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties via a so-called fuzzy Lyapunov function which is a multiple Lyapunov function. The fuzzy Lyapunov function is defined by fuzzily blending quadratic Lyapunov functions. First, the Takagi-Sugeno (T-S) fuzzy model with parametric uncertainties is used as the model for the uncertain nonlinear system. Based on the fuzzy Lyapunov function approach and a parallel distributed compensation (PDC) scheme, we give stabilization conditions for closed-loop fuzzy systems with parametric uncertainties. Second, all the conditions are formulated in the format of linear matrix inequalities (LMIs) and contain upper bounds of the time derivative of premise membership functions as LMI variables. Finally, the T-S fuzzy model of the Chaotic Lorenz system, which has complex nonlinearity, is developed as a test bed. A numerical example of the Chaotic Lorenz system is given to illustrate the utility or the fuzzy Lyapunov function approach.
引用
收藏
页码：514 / 519
页数：6
相关论文
共 50 条
  • [41] Lyapunov Based Multiple Model Predictive Control: An LMI Approach
    Abdollahpouri, Mohammad
    Khaki-Sedigh, Ali
    Fatehi, Alireza
    2012 AMERICAN CONTROL CONFERENCE (ACC), 2012, : 1998 - 2003
  • [42] Observer Design of Discrete Time T-S Fuzzy Systems With Measurable Premise Variables Based on Fuzzy Lyapunov Function Approach
    Rizk, Mohamed R. M.
    Tayel, Mazhar B.
    Saed, Walied M.
    2016 3RD INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE), 2016, : 1015 - 1018
  • [43] Novel LMI-Based Stability Conditions for Interval Type-2 T-S Fuzzy Logic Control Systems
    Yu, Gwo-Ruey
    Cheng, Tzu-Fu
    2015 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATICS AND BIOMEDICAL SCIENCES (ICIIBMS), 2015, : 412 - 417
  • [44] Design of Fuzzy Control T-S for Wind Energy Conversion System based PMSG using LMI Approach
    Chatri, Chakib
    Ouassaid, Mohammed
    2018 IEEE 5TH INTERNATIONAL CONGRESS ON INFORMATION SCIENCE AND TECHNOLOGY (IEEE CIST'18), 2018, : 466 - 471
  • [45] Relaxed stability for T-S fuzzy systems using line-integral fuzzy lyapunov function
    Jeung E.T.
    Journal of Institute of Control, Robotics and Systems, 2020, 26 (03) : 148 - 153
  • [46] Design of T-S Fuzzy-Model-Based Controller for Depth Control of Autonomous Underwater Vehicles with Parametric Uncertainties
    Jun, Sung Woo
    Kim, Do Wan
    Lee, Ho Jae
    2011 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2011, : 1682 - 1684
  • [47] Robust control and simulation of a class of T-S fuzzy systems with parametric uncertainties
    Institute of Electrical Automation, Control Science and Engineering Research Center, Southern Yangtze University, Wuxi 214122, China
    Hua Dong Li Gong Da Xue/J East China Univ Sci Technol, 2006, 7 (884-888):
  • [48] Feedback Controller Design for T-S Fuzzy Control Systems Based on Lyapunov Approach
    Chen, Zhaona
    Wang, Qimning
    Jing, Yuanwei
    Wang, Hongwei
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 939 - +
  • [49] Intelligent Control: A T-S Fuzzy Model Based Approach
    Feng, Gang
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : XXIV - XXIV
  • [50] A New Fuzzy Lyapunov Function Approach to Stability and Stabilization for Continuous-Time T-S Fuzzy Systems
    Li, Lizhen
    Wang, Weiqun
    ICMS2010: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION ICMS2010, VOL 5: APPLIED MATHEMATICS AND MATHEMATICAL MODELLING, 2010, : 14 - 19
12345