Functional approximation-based adaptive sliding control with fuzzy compensation for an active suspension system

Since it is difficult to establish an accurate dynamic model of a physical active suspension system for a model-based control design, various model-free approaches have been introduced in this field of application. This paper proposes a functional approximation-based adaptive sliding controller with fuzzy compensation for a quarter-car active suspension system. The functional approximation technique is employed to represent the unknown function and release the model-based requirement of a sliding mode control. In addition, a self-tuning fuzzy scheme is introduced to compensate the model approximation error for improving the control performance. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters can be derived from the Lyapunov function directly for guaranteeing the system stability. The simulation results show that the proposed control approach can suppress effectively the vibration amplitude of this suspension system under severe external uncertainties. The dynamic performance of this proposed controller is compared with that of the adaptive sliding controller without fuzzy compensation to show the performance improvement of the inducing of fuzzy control loop.