Performance Analysis of the Rule-Optimized Fuzzy-Logic Controller for Semi-Active Suspension

This paper presents a performance analysis study for the Rule-Optimized controller of a semi-active suspension system. The Rule-Optimized controller is based on a Fuzzy Logic control scheme which offers new opportunities in the improvement of vehicle ride performance. An eleven degree of freedom full vehicle ride dynamics model is developed and validated through laboratory tests performed on a hydraulic four-poster shaker. An optimization process is applied to obtain the optimum Fuzzy Logic membership functions and the optimum rule-base of the semi-active suspension controller. The global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle is determined through discrete optimization with Genetic Algorithm (GA). The performance analysis of the controller is performed by evaluating the Rule-Optimized controller performance under different driving conditions; including different road profiles, different vehicle speeds and different vehicle loadings. The results show that, the Fuzzy-Logic based Rule-Optimized controller for semi-active suspension provides significant improvements in both ride comfort and road holding performance of the vehicle under different operating conditions.