Neuro-fuzzy fitness in a genetic algorithm for optimal fuzzy controller design

This paper describes an evolutionary genetic algorithm approach for the optimization of a fuzzy reactive controller applied to the design of a fuzzy controller for 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.