Speed control of permanent magnet synchronous motor by using fuzzy logic controllers having different inference methods

Fuzzy logic is an artificial intelligence control method that is used for controlling time variant and nonlinear systems having model uncertainty. Alternative current motors contain unidentified and nonlinear system dynamics in their structures. Therefore, fuzzy logic controllers have been widely used in controlling of these motors. In this study, permanent magnet synchronous motor that is one of the alternative current motors has been controlled with fuzzy logic controllers. Input and output membership functions, rule based inference mechanisms and defuzzification processes have been realized in the designed controllers. Simulation results that are obtained under different load and speed operating conditions have been analyzed in the studies. Then performances of Mamdani, Larsen and Tsukamoto fuzzy inference methods have been compared. When the obtained results have been evaluated, It’s been seen that Larsen and Tsukamoto fuzzy inference methods have better performance