PSO Optimized Fuzzy Logic Controller for Active Suspension System

Abstract

In this paper, Particle Swarm Optimization (PSO) is developed for tuning Fuzzy Logic Controller applied to Active suspension system. First the controller is designed according to Fuzzy Logic rules for disturbance rejection to reduce unwanted vehicle’s motion. Then the Fuzzy Logic Controller (FLC) is optimized with PSO and Genetic Algorithm (GA) so as to obtain optimal adjustment of the scaling factors, membership functions and the number of fuzzy control rules. R.M.S. value of the body acceleration is considered as the performance index. The relative performances of the two algorithms are compared. Digital simulation results demonstrate that the PSO tuned Fuzzy Logic Controller based active suspension system exhibits an improved ride comfort and good road holding ability than its counterparts.