INTEllIGENT CONTROL OF AUTOMOTIVE SEMI-ACTIVE SUSPENSION WITH UNCERTAIN FACTORS

Taking a nonlinear semi-active magnetal-rehological suspension model of a quarter car as a research objective, a concrete intelligent control strategy that associates neural network technique with a sliding mode-variable-structure-control method is presented on the basis of a nonlinear system in an unknown dynamic status. It suppresses the vibration of a suspension system effectively and can improve the ride performance and ride comfort. The unknown part of the nonlinear dynamic model and outside disturbance are estimated using neural network theory which has on-line learning ability and the upper boundary of the unknown part is determained.. The state variables approach the original point along the constructive sliding mode by designing the reasonable self adaptive law of neural network. The stability analysis conforms that this control method is convergent and robust to the unknown dynamic part in global. Simulation results make sure the validity of the control method, and the control voltage of the damper is obtained.