Model parameter identification for vehicle vibration control with magnetorheological dampers using computational intelligence methods

Abstract The parameter identification of magnetorheological dampers by an inverse method is proposed. A modified Bouc-Wen modified dynamic model is considered and its parameters are obtained by using genetic algorithms. The experimental data consist of time histories of current, displacement, velocity, and force measured for both constant and variable current. The model parameters are determined using a set of experimental measurements corresponding to different constant current values and the resulting model is validated on the data measured for variable current. Based on this model a semi-active control of vehicle suspension is studied and a fuzzy controller is developed to reduce the chattering effect.