Toward better ride performance of vehicle suspension system via intelligent control

The authors focus on developing a robust control algorithm for vehicle suspension systems while providing a comfortable ride. Specifically, a model reference self-tuning fuzzy logic control scheme which consists of a primary and a secondary controller is proposed. The primary controller performs the major control function for the actual sprung mass acceleration. The secondary controller is used to tune the output membership function of the primary fuzzy logic controller online so that it is capable of adapting process variations such as sprung mass change, spring and damper rate variations, and harsh road conditions. Simulation results show that the performance of the suspension system controlled by the proposed controller is much better than that of a passive suspension system. The simulations and a comparison study also demonstrate the superior robustness of the proposed fuzzy logic controller over the conventional controller for an active vehicle suspension system.<<ETX>>

[1]  Shuo-Huan Hsu,et al.  A self-learning fuzzy controller , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[2]  C. Harris,et al.  Phase plane analysis tools for a class of fuzzy control systems , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[3]  J. D. Robson,et al.  ROAD SURFACE DESCRIPTION IN RELATION TO VEHICLE RESPONSE , 1977 .

[4]  John Yen,et al.  Performance evaluation of a self-tuning fuzzy controller , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[5]  Myoungho Sunwoo,et al.  Investigation of Adaptive Control Approaches for Vehicle Active Suspension Systems , 1991, 1991 American Control Conference.

[6]  Aleksander Hac,et al.  Optimal Semi-Active Suspension with Preview based on a Quarter Car Model , 1991, 1991 American Control Conference.

[7]  J. D. Robson ROAD SURFACE DESCRIPTION AND VEHICLE RESPONSE , 1979 .

[8]  L. Zheng,et al.  A practical guide to tune of proportional and integral (PI) like fuzzy controllers , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[9]  K. C. Cheok,et al.  An application of explicit self-tuning controller to vehicle active suspension systems , 1990, 29th IEEE Conference on Decision and Control.

[10]  Celal Batur,et al.  Adaptive expert control , 1991 .