Abstract
Control algorithms are developed for force control in an active vehicle suspension design using genetic algorithms with both quarter car and half car models. The main function of active suspension is to support the vehicle body and isolates the road unevenness to provide ride comfort. Besides, the other important objective is to maintain the contact between tire and road and to minimize the variation of tire deflection for handling control. In this study, force cancellation, virtual damper, skyhook damper, and road-following concepts are proposed to design the force controller for achieving better ride and handling quality. Furthermore, a new approach incorporates the constraints of maximum suspension strokes in the objective function to evaluate the compactness of the suspension working space, as opposed to the traditional integral quadratic form of suspension displacement. Genetic algorithms are employed to obtain a more effective search for optimum control parameters. In addition, a nonlinear model is introduced and a fuzzy control scheme is proposed to deal with the nonlinear tire characteristic, tire deflection limits, and suspension stroke limitations. Computer simulations are performed to verify the proposed control scheme. It is shown both ride comfort and handling quality are greatly improved without exceeding the suspension stroke constraints.