Quadratic Optimal Control with Disturbance Attenuation for Uncertain Continuous-Time T-S Fuzzy Systems

被引:4
作者
Horng, Wen-Ren [1 ]
Fang, Chun-Hsiung [1 ]
Chou, Jyh-Horng [1 ]
机构
[1] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung, Taiwan
关键词
Disturbance attenuation; Hybrid Taguchi-genetic algorithm; Non-quadratic Lyapunov function; Optimal control; Orthogonal functions; Takagi-Sugeno (T-S) fuzzy systems; LYAPUNOV FUNCTION-APPROACH; H-2 GUARANTEED COST; NONLINEAR-SYSTEMS; STABILITY; DESIGN; STABILIZATION;
D O I
10.1080/03772063.2016.1229139
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, an algebraically computational method is proposed to synthesize non-parallel-distributed-compensation (non-PDC) fuzzy controller such that (1) the prescribed disturbance attenuation level for the uncertain continuous-time Takagi-Sugeno (T-S) fuzzy system can be achieved, and (2) a quadratic integral performance index for nominal T-S fuzzy model-based control system can be minimized. We first derive relaxed linear matrix inequality (LMI) conditions by non-quadratic Lyapunov function and non-PDC fuzzy controller to meet prescribed disturbance attenuation level for the uncertain T-S systems. Then by using LMIs and orthogonal function array, the robust quadratic optimal control with disturbance attenuation for uncertain T-S fuzzy system is transformed into constrained-optimization problem represented by algebraic equations and LMI constraints. For static constrained-optimization problem, the HTGA is employed to search the gains non-PDC controllers. Therefore, the robust optimal controller design problem can be greatly simplified with the proposed method. The design example is given to demonstrate the applicability of the proposed approach.
引用
收藏
页码:98 / 108
页数:11
相关论文
共 28 条
[21]   A multiple Lyapunov function approach to stabilization of fuzzy control systems [J].
Tanaka, K ;
Hori, T ;
Wang, HO .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2003, 11 (04) :582-589
[22]  
Tanaka K., 2001, Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, DOI DOI 10.1002/0471224596
[23]   A Descriptor system approach to fuzzy control system design via fuzzy Lyapunov functions [J].
Tanaka, Kazuo ;
Ohtake, Hiroshi ;
Wang, Hua O. .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2007, 15 (03) :333-341
[24]   Hybrid Taguchi-genetic algorithm for global numerical optimization [J].
Tsai, JT ;
Liu, TK ;
Chou, JH .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2004, 8 (04) :365-377
[25]   Parameterized linear matrix inequality techniques in fuzzy control system design [J].
Tuan, HD ;
Apkarian, P ;
Narikiyo, T ;
Yamamoto, Y .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2001, 9 (02) :324-332
[26]   H2 guaranteed cost fuzzy control for uncertain nonlinear systems via linear matrix inequalities [J].
Wu, HN ;
Cai, KY .
FUZZY SETS AND SYSTEMS, 2004, 148 (03) :411-429
[27]   H∞ Fault Detection for Networked Mechanical Spring-Mass Systems With Incomplete Information [J].
Yan, Huaicheng ;
Qian, Fengfeng ;
Zhang, Hao ;
Yang, Fuwen ;
Guo, Ge .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2016, 63 (09) :5622-5631
[28]  
Zhang H., IEEE T IND INF UNPUB, DOI [10.1109/TII.2016.2569556, DOI 10.1109/TII.2016.2569556]