DIRECT TORQUE CONTROL OF INDUCTION MOTORS BY USE OF THE GMR NEURAL NETWORK

This paper deals with the application of the General Mapping Regressor (GMR) neural network to the direct torque control DTC of an induction motor. In particular it shows that the GMR neural network is able to correctly learn the classical DTC, as well as any other more involved control strategy. A suitable test bench has been set up in order to verify the performance of the neural controller.