The Study on the Membership Function Shape of Fuzzy Controller Optimization

Abstract

Since it is difficult to determine a fuzzy controller parameters, which need to match the test car's complex nonlinear dynamic characteristics. Based on particle swarm optimization algorithm, a fuzzy self-tuning controller parameters optimization method is developed. The controller is reconstructed by using particle swarm optimization, which can randomly chosen values in the value range of membership function's shape point in many times. And to keep track of the objective function as best, the membership function shape optimization problem of fuzzy self-tuning controller is solved. The simulation results show that the optimized controller has good control performance, which can get controller parameters by using particle swarm optimization method.