A Novel Membership Functions Dependent Robust Control for Suspension Systems

ABSTRACT Active vehicle suspension systems play a vital role in isolating vibration between the pavement and chassis. In this paper, to further enhance the driving comfort level while maintaining correlative suspension operation safety, a novel membership functions (MFs)‐dependent‐based optimization control policy is first proposed for quarter nonlinear active vehicle suspension systems under a Takagi‐Sugeno (T‐S) fuzzy framework. In view of that, different subsystems may have diverse interference attenuation upper boundaries. We combine the information of MFs with a common performance index, such that for the fuzzy rules that have high proportions, a relatively small disturbance attenuation index can be obtained. Compared with the existing traditional method, the practical response of the interference attenuation index is efficaciously decreased, thus a superior driving comfort level and better suspension requirements manifestations can be obtained. Lastly, an illustrative example is presented to testify to the superiorities and advantages of the proposed novel robust optimization control algorithm.