Adaptive sliding controller for active suspension system

Active suspension systems are designed to provide desirable ride comfort and handling capability in the automotive industry. Since the active suspension system has nonlinear and time-varying characteristic, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, a functional approximation based adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The functional approximation technique is employed to represent the unknown functions, it releases the model-based requirement of the sliding mode control. In addition, a fuzzy scheme with online learning ability is employed to compensate the modeling error of the functional approximation with finite number of terms for reducing the implementation difficulty. To guarantee the control system stability, the update laws of the approximation function´s coefficients and the fuzzy tuning parameters are derived from the Lyapunov theorem. The proposed controller is employed on a quarter-car numerical model. The numerical results show that the proposed controller suppresses the oscillation amplitude of this suspension system effectively.