To solve the nonlinearity and dynamic uncertainty of magnetorheological (MR) suspension system, a fuzzy logic control strategy based on a hybrid Taguchi genetic algorithm (HTGA) is proposed for the MR suspension. As the first step, a full car dynamic model with four MR dampers is developed. The task of vibration control of vehicle is decomposed into three independent fuzzy control modules: a heave motion control module, a pitch motion control module and a roll motion control module. The membership functions and control rules of the three control modules are designed. Subsequently, a HTGA is adopted to simultaneously tune the membership functions and control rules of the fuzzy controller. At last, road test is performed to validate the proposed control strategy. The results of the road test indicate that the MR suspension system with fuzzy controller tuned by HTGA can reduce greatly the peak-peak acceleration of the vertical vibration of vehicle under bump road, has smaller root mean square of acceleration, and improve the ride comfort compared to the passive suspension system. Moreover, its control performance is superior to the simple fuzzy logic control strategy.