An LMI-Based Controller Design of Uncertain Nonlinear Systems using Takagi-Sugeno Fuzzy Region Model

被引:0
|
作者
Bai, Shengjian [1 ]
Huang, Xinsheng [2 ]
Xu, Wanying [2 ]
Zhang, Lundong [2 ]
机构
[1] Natl Univ Def Technol, Coll Mechatron Engn & Automat, Changsha 410073, Hunan, Peoples R China
[2] Natl Univ Def Technol, Changsha 410073, Hunan, Peoples R China
关键词
STABILITY ANALYSIS; REGULATORS; FEEDBACK;
D O I
10.1109/ROBIO.2009.5420849
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Robust control of a class of uncertain Takagi-Sugeno (T-S) fuzzy system is investigated in the paper by using fuzzy region concept. The general uncertain T-S fuzzy model with Standard Fuzzy Partition (SFP) inputs is converted into fuzzy region ones. A Fuzzy Region Controller (FRC) is designed based on the fuzzy region concept, and sub-models in a fuzzy region share the same FRC. The relaxed stability conditions for closed-loop fuzzy region systems are derived by using Piecewise Smooth Quadratic (PSQ) Lyapunov function in terms of Linear Matrix Inequalities (LMIs). The derived stability condition, which only requires finding a local common positive definite symmetric matrix P in each operating region, can reduce the conservatism and difficulty in existing stability conditions. Finally, the feasibility and validity of this approach are demonstrated by a numerical example.
引用
收藏
页码:1209 / +
页数:2
相关论文
共 50 条
  • [1] LMI-based design of stabilizing fuzzy controllers for nonlinear systems described by Takagi-Sugeno fuzzy model
    Park, J
    Kim, J
    Park, D
    FUZZY SETS AND SYSTEMS, 2001, 122 (01) : 73 - 82
  • [2] LMI-Based design of optimal controllers for Takagi-Sugeno fuzzy systems
    Park, J
    Park, Y
    Kwak, K
    Hong, JH
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004, 2004, 3070 : 972 - 977
  • [3] LMI-based tracking control for Takagi-Sugeno fuzzy model
    Abdelkrim, Afef
    Ghorbel, Chekib
    Benrejeb, Mohamed
    International Journal of Control and Automation, 2010, 3 (02): : 21 - 36
  • [4] LMI approach for Takagi-Sugeno fuzzy controller design
    Khaber, F
    Hamzaoui, A
    Zehar, K
    PROCEEDINGS OF THE 7TH WSEAS INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL, MODELING AND SIMULATION, 2005, : 357 - 362
  • [5] Observer Based Controller For Nonlinear Systems Using Takagi-Sugeno Fuzzy Model
    Shodan, A. R.
    Singh, Devender
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO'16), 2016,
  • [6] An augmented system approach for LMI-based control design of constrained Takagi-Sugeno fuzzy systems
    Anh-Tu Nguyen
    Marquez, Raymundo
    Dequidt, Antoine
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2017, 61 : 96 - 102
  • [7] On the conservatism reduction of LMI-based stabilization conditions for Takagi-Sugeno fuzzy systems
    Lamloumi, Lamjed
    Yaich, Adel
    Chaari, Abdelkader
    2015 4TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2015, : 134 - 139
  • [8] Improved LMI-based Conditions for Quadratic Stabilization of Takagi-Sugeno Fuzzy Systems
    Xie, Wei
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 2634 - 2639
  • [9] Stable nonlinear controller design for a Takagi-Sugeno fuzzy model
    Choon-Young Lee
    Tae-Dok Eom
    Ju-Jang Lee
    Artificial Life and Robotics, 2001, 5 (1) : 20 - 25
  • [10] Takagi-Sugeno Dynamic Neuro-Fuzzy Controller of Uncertain Nonlinear Systems
    Cervantes, Jorge
    Yu, Wen
    Salazar, Sergio
    Chairez, Isaac
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2017, 25 (06) : 1601 - 1615