Performance Analysis of Fuzzy Logic Controllers Optimized by Using Genetic Algorithm

There are many different design parameters such as membership functions, scaling factors, inference and defuzzification methods in the structures of fuzzy logic controllers. Most of the time, it is difficult to determine the parameters accurately even with the help of experts. For this purpose, genetic algorithm one of the heuristic optimization techniques is used to facilitate the design of optimal fuzzy logic controller in this study. Fuzzy logic controllers used in the studies are designed with entirely user-defined software instead of toolboxes. Performances of the designed controllers have been analyzed through simulation studies performed on the permanent magnet synchronous motor. Results obtained from the simulation studies have showed that fuzzy logic controllers optimized based on ITAE performance indice have better performance.