Rule Optimized Fuzzy Logic Controller for Full Vehicle Semi-Active Suspension

This paper presents a new and effective control concept for semi-active suspension systems. The proposed controller uses a Fuzzy Logic scheme which offers new opportunities in the improvement of vehicle ride performance. The Fuzzy Logic scheme tunes the controller to treat the conflict requirements of ride comfort and road holding parameters within a specified range of the suspension deflection. An eleven degree of freedom full vehicle ride dynamics model is constructed and validated through laboratory tests performed on a hydraulic four-poster shaker. A new optimization process for obtaining the optimum Fuzzy Logic membership functions and the optimum rule-base of the proposed semi-active suspension controller is proposed. Discrete optimization has been performed with a Genetic Algorithm (GA) to find the global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle. The proposed Fuzzy Logic semi-active controller is compared to the optimum Linear Quadratic Regulator (LQR) semi-active controller and the optimum passive suspension system in terms of ride comfort and road holding. The results showed that the proposed semi-active suspension system controller provides significant improvements in both ride comfort and road holding performance of the vehicle.