Optimal Fuzzy Controller, using a Genetic Algorithm for a Ball on Wheel System

Abstract

The process of building a fuzzy controller for the Ball on Wheel problem raised an issue with the optimization of the controller parameters. For non-linear systems the parameter values of the controller are based on a subjective estimate and a trial-and-error approach. This is a time-consuming human task, which could be automated. The information obtained from the visualized simulation results gave us the opportunity to increase the controllable area, using a genetic algorithm (GA), by tuning the parameters of the fuzzy membership methods.