Output tracking control for fuzzy systems via output feedback design

被引:104
作者
Lian, Kuang-Yow [1 ]
Liou, Jeih-Jang [1 ]
机构
[1] Chung Yuan Christian Univ, Dept Elect Engn, Chungli 32023, Taiwan
关键词
control application; linear matrix inequality (LMI) approach; observer design; output tracking; Takagi-Sugeno (T-S) fuzzy systems;
D O I
10.1109/TFUZZ.2006.876725
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Fuzzy observer-based control design is proposed to deal with the output tracking problem for nonlinear systems. For the purpose of tracking design, the new concept of virtual desired variables and, in turn the so-called generalized kinematics are introduced to simplify the design procedure. In light of this concept, the design procedure is split into two steps: i) Determine the virtual desired variables from the generalized kinematics; and ii) Determine the control gains just like solving linear matrix inequalities for stabilization problem. For immeasurable state variables, output feedback design is proposed. Here, we focus on a common feature held by many physical systems where their membership functions of fuzzy sets satisfy a Lipschitz-like property. Based on this setting, control gains and observer gains can be designed separately. Moreover, zero tracking error and estimation error are concluded. Three different types of systems, including nonlinear mass-spring systems, dc-dc converters, and induction motors are considered to demonstrate the design procedure. Their satisfactory simulation results verify the proposed approach.
引用
收藏
页码:628 / 639
页数:12
相关论文
共 17 条
  • [1] Boy S., 1994, Linear MatrixInequalities in System and Control Theory
  • [2] Chen BS, 2000, IEEE T FUZZY SYST, V8, P249, DOI 10.1109/91.855915
  • [3] CHEN XJ, 1999, SHIJIE HUAREN XIAOHU, V7, P5
  • [4] Farinwata SS, 2000, FUZZY CONTROL: SYNTHESIS AND ANALYSIS, P203
  • [5] Han YL, 2000, GLIA, V30, P1
  • [6] Jadbabaie A, 1997, IEEE DECIS CONTR P, P3347, DOI 10.1109/CDC.1997.652362
  • [7] On the stability issues of linear Takagi-Sugeno fuzzy models
    Joh, J
    Chen, YH
    Langari, R
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1998, 6 (03) : 402 - 410
  • [8] Khalil HK., 1992, NONLINEAR SYSTEMS
  • [9] New approaches to relaxed quadratic stability condition of fuzzy control systems
    Kim, E
    Lee, H
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2000, 8 (05) : 523 - 534
  • [10] Krause P.C., 1994, ANAL ELECT MACHINERY