High Performance Direct Torque Control of a PMSM using Fuzzy Logic and Genetic Algorithm

This investigation improves the performance of a direct torque controlled permanent magnet synchronous motor (PMSM) using both genetic algorithm (GA) and fuzzy logic. In this approach electromagnetic torque error, stator flux linkage error and stator flux angle are fuzzified using three appropriate fuzzy sets. Therefore the best voltage space vector has been selected in order to minimize torque, flux and current ripples. In this paper direct torque control (DTC) of a PMSM drive is simulated using both conventional table based and fuzzy methods and the PI speed controller is tuned using GA. A comparative study between conventional DTC and proposed approach shows that not only the speed response of the controller has been improved but also torque, flux and stator current ripples have significantly been reduced without any effective change of the inverter switching frequency.