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New developments in road profile measurement systems and in semi-active damper technology promote the application of preview control strategies to vehicle suspension systems. This paper details a new semi-active suspension control approach in which a rule-optimized Fuzzy Logic controller is enhanced through preview capability. The proposed approach utilizes an optimization process for obtaining the optimum membership functions and the optimum rule-base of the preview enhanced Fuzzy Logic controller. The preview enhanced Fuzzy Logic controller uses the feedforward road input information and the feedback vehicle state information as the controller inputs. An eleven degree of freedom full vehicle model, which is validated through laboratory tests performed on a hydraulic four-poster shaker, is used for the controller synthesis.

Following the developments in controlled suspension system components, the studies on the vertical dynamics analysis of vehicles increased their popularity in recent years. The objective of this study is to develop a semi-active suspension system controller using Adaptive-Fuzzy Logic control theories together with Kalman Filter for state estimation. A quarter vehicle ride dynamics model is constructed and validated through laboratory tests performed on a hydraulic four-poster shaker. A Kalman Filter algorithm is constructed for bounce velocity estimation, and its accuracy is verified through measurements performed with external displacement sensors. The benefit of using adaptive control with Fuzzy-Logic to maintain the optimal performance over a wide range of road inputs is enhanced by the accuracy of Kalman Filter in estimating the controller inputs. A gradient-based optimization algorithm is applied for improving the Fuzzy-Logic controller parameters.

Due to the importance of the fast transportation under every circumstance, the transportation process may require a high speed heavy vehicle from time to time, which may turn the transportation process more unsafe. Due to that fact the truck safety during braking and the ride comfort during long distance travelling with high speeds should be improved. Therefore, the aim of this work is to develop a control system which combines the suspension and braking systems. The control system consists of three controllers; the first one for the active suspension system of the truck body and cab, the second one for the ABS and, the third for the integrated control system between the active suspension system and the ABS. The control strategy is also separated into two strategies.

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.

Semi-active suspension offers variety of damping force range which demands greater need to optimize the top mount to ensure multiple objectives of ride comfort, harshness and safety can be achieved. For this purpose, this paper proposes a numerical optimization procedure for improving the harshness performance of the vehicle through the adjustment of the damper top mount characteristics of the semi-active suspension system. The proposed optimization process employs a frequency dependent combined objective function based on ride comfort and harshness evaluation. A detailed and accurate damper top mount mathematical model is implemented inside a validated full vehicle model to provide a realistic simulation environment for the optimization study. The semi-active suspension system employs a Rule-Optimized Fuzzy-Logic controller. The ride comfort and harshness of the full vehicle are evaluated by analyzing the body acceleration in different frequency ranges.