| The vehicle suspension system is the power transmission junction device between the wheel and the vehicle chassis, which relieve the impact of external disturbance and ensures the vehicle ride comfort and handling stability. Active suspension system is superior in controlling quality to the passive suspension, can active prompt adjustment and produce a desired suspension control between wheel and body according to the situation of road, to suppress the vibration of the body and make the suspension in optimal reducing vibration condition. Control objective of active suspension system is to obtain the good ride comfort and the operation stability, the traditional control theory and the method is very difficult to achieve. Fuzzy control imitating the human mind is an intelligent control method and is suitable for active suspension control. The kernel of the FLC is a set of linguistic control rules, which captures human thinking and organizes the approximate to determine control decisions for the process. The conventional fuzzy control rules are established by the knowledge and experience of expertise or skilled operator. Genetic algorithm (GA) as a stochastic optimization algorithm is motivated by the mechanisms of natural selection and evolutionary genetics.In this paper, ADAMS/View software is utilized to complete the multi-body model of active suspension system. In order to control the suspension system efficiently, a fuzzy logic controller is developed in Matlab/Simulink environment. Then, GA is used to construct the optimal decision making logic of the FLC for active suspension system. To verify the performance of the genetic algorithm-based controller, simulations were simulated with random road profile at 30m/s to demonstrate the effectiveness of the proposed control system in comparison with the passive suspension response. It was shown that this developed fuzzy logic controller based on genetic algorithm enhances the performance of the full car suspension system significantly.
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