Observer-Based Robust Adaptive Fuzzy Control for MIMO Nonlinear Uncertain Systems with Delayed Output

被引:1
作者
Chiang, Chiang Cheng [1 ]
机构
[1] Tatung Univ, Dept Elect Engn, Taipei 104, Taiwan
关键词
TRACKING CONTROL; NEURAL CONTROL; DESIGN; STABILIZATION; FEEDBACK;
D O I
10.1155/2013/215201
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An observer-based robust adaptive fuzzy control scheme is presented to tackle the problem of the robust stability and the tracking control for a class of multiinput multioutput (MIMO) nonlinear uncertain systems with delayed output. Because the nonlinear system functions and the uncertainties of the controlled system including structural uncertainties are supposed to be unknown, fuzzy logic systems are utilized to approximate these nonlinear system functions and the upper bounded functions of the uncertainties. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is also estimated. In addition, the state observer based on state variable filters is designed to estimate all states which are not available for measurement in the controlled system. By constructing an appropriate Lyapunov function and using strictly positive-real (SPR) stability theorem, the proposed robust adaptive fuzzy controller not only guarantees the robust stability of a class of multivariable nonlinear uncertain systems with delayed output but also maintains a good tracking performance. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control approach.
引用
收藏
页数:12
相关论文
共 31 条
[1]  
Chen BS, 1996, IEEE T FUZZY SYST, V4, P32, DOI 10.1109/91.481843
[2]  
Chiang CC, 2003, IEEE IJCNN, P2394
[3]  
Chiang CC, 2000, IEEE DECIS CONTR P, P1315, DOI 10.1109/CDC.2000.912038
[4]   Robust adaptive control of uncertain MIMO non-linear systems - feedforward Takagi-Sugeno fuzzy approximation based approach [J].
Chiu, CS .
IEE PROCEEDINGS-CONTROL THEORY AND APPLICATIONS, 2005, 152 (02) :157-164
[5]   A new approach to state observation of nonlinear systems with delayed output [J].
Germani, A ;
Manes, C ;
Pepe, P .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2002, 47 (01) :96-101
[6]  
Isidori A., 1989, Nonlinear Control Systems
[7]   Observer-based indirect adaptive fuzzy sliding mode control with state variable filters for unknown nonlinear dynamical systems [J].
Kung, CC ;
Chen, TH .
FUZZY SETS AND SYSTEMS, 2005, 155 (02) :292-308
[8]   Adaptive fuzzy control of a class of MIMO nonlinear systems [J].
Labiod, S ;
Boucherit, MS ;
Guerra, TM .
FUZZY SETS AND SYSTEMS, 2005, 151 (01) :59-77
[9]   Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems [J].
Leu, YG ;
Lee, TT ;
Wang, WY .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1999, 29 (05) :583-591
[10]   A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems [J].
Li, HX ;
Tong, SC .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2003, 11 (01) :24-34