Direct Torque Control Using Fuzzy and Neural as Switching Vector Selector for Doubly Fed IM

The conventional Direct Torque Control approach has some drawbacks such as high torque ripple and switching frequency, which is varying with speed, load torque and the selected hysteresis bands, this paper discuss the application of neural network and fuzzy logic on DTC of Doubly fed induction motor DFIM, the proposed techniques having the advantages of low torque and flux ripples. Simulation results emphasize the good performance of the fuzzy and neural techniques.