Non-fragile output feedback H∞ vehicle suspension control using genetic algorithm

被引:100
作者
Du, HP
Lam, J
Sze, KY
机构
[1] Univ Hong Kong, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China
[2] Shanghai Jiao Tong Univ, Natl Key Lab Vibrat Shock & Noise, Shanghai 200030, Peoples R China
关键词
static output feedback; non-fragile H-infinity control; active suspension;
D O I
10.1016/j.engappai.2003.09.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents an approach to design static output feedback and non-fragile static output feedback H-infinity controllers for active vehicle suspensions by using linear matrix inequalities and genetic algorithms. A quarter-car model with active suspension system is considered in this paper. By suitably formulating the minimization problem of the sprung mass acceleration, suspension deflection and tyre deflection, a static output feedback H-infinity controller and a non-fragile static output feedback H-infinity controller are obtained. The controller gain is naturally constrained in the design process. The approach is validated by numerical simulation which shows that the designed static output feedback H-infinity controller can achieve good active suspension performance in spite of its simplicity, and the non-fragile static output feedback H-infinity controller has significantly improved the non-fragility characteristics over controller gain variations. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:667 / 680
页数:14
相关论文
共 47 条
[1]  
Abdellahi E, 2000, P AMER CONTR CONF, P4041, DOI 10.1109/ACC.2000.876981
[2]   Sliding mode neural network inference fuzzy logic control for active suspension systems [J].
Al-Holou, N ;
Lahdhiri, T ;
Joo, DS ;
Weaver, J ;
Al-Abbas, F .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2002, 10 (02) :234-246
[3]   On control relevant criteria in H∞ identification [J].
Boling, JM ;
Makila, PM .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1998, 43 (05) :694-700
[4]  
Calafiore G, 1998, IEEE DECIS CONTR P, P3335, DOI 10.1109/CDC.1998.758215
[5]   A probabilistic framework for problems with real structured uncertainty in systems and control [J].
Calafiore, G ;
Dabbene, F .
AUTOMATICA, 2002, 38 (08) :1265-1276
[6]   Stochastic algorithms for exact and approximate feasibility of robust LMIs [J].
Calafiore, G ;
Polyak, BT .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2001, 46 (11) :1755-1759
[7]   Randomized algorithms for probabilistic robustness with real and complex structured uncertainty [J].
Calafiore, GC ;
Dabbene, F ;
Tempo, R .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (12) :2218-2235
[8]  
Camino J. F., 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), P3168, DOI 10.1109/ACC.1999.782348
[9]   Static output feedback stabilization: An ILMI approach [J].
Cao, YY ;
Lam, J ;
Sun, YX .
AUTOMATICA, 1998, 34 (12) :1641-1645
[10]  
Chen H, 2001, P AMER CONTR CONF, P2646, DOI 10.1109/ACC.2001.946275