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