Optimal Fuzzy Controller: Rule Base Optimized Generation

Abstract

A novel Fuzzy Logic (FL) controller design methodology is presented. The method utilizes an in-house developed Particle Swarm Optimization (PSO) binary search algorithm to generate the rules for the Fuzzy Logic controller rule-base stage without any human experience intervention. The proposed technique is compared with the well-established Lyapunov based Fuzzy Logic controller design in generating such rules. Finally, the controller's effectiveness and performance are tested, verified and validated using an electrical traction elevator control application. The designed controller's results were compared with the traditional ubiquitous Proportional-Integral-Derivative (PID) controller and classical Logic controllers.