On the optimum design of fuzzy logic controller for trajectory tracking using evolutionary algorithms

Differential evolution (DE) and genetic algorithms (GA) are population based search algorithms that come under the category of evolutionary optimization techniques. In the present study, these evolutionary methods have been utilized to conduct the optimum design of the fuzzy controller for mobile robot trajectory tracking. Comparison between their performances has also been conducted. In this paper we present a fuzzy controller to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions would be optimized by evolutionary algorithms in order to obtain more acceptable results.