Genetic algorithm with a Neuro-Fuzzy fitness function for optimal fuzzy controller design

Abstract

This paper describes an evolutionary algorithm approach for the optimization of a fuzzy reactive controller applied to a mobile robot. The algorithm will optimize the Fuzzy Inference System evaluating the performance of each individual with a Neuro-Fuzzy fitness function that considers the robots covered distance, time used, battery life and the pattern of the trajectory.