Type-1 and Type-2 fuzzy logic controller design using a Hybrid PSO-GA optimization method

In this paper we propose a Hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC) to minimize the steady state error of a plant's response. We test the optimal FLC obtained by the Hybrid PSO-GA method using benchmark control plants and an autonomous mobile robot for trajectory tracking control. The bio-inspired method is used to find the parameters of the membership functions of the FLC to obtain the optimal controller for the respective plants. Simulation results show the feasibility of the proposed approach for these control applications. A comparison is also made among the proposed Hybrid PSO-GA, with GA and PSO to determine if there is a significant difference in the results.