Speed and Torque Control of an Induction Motor with Ann Based Dtc

Due to advantages such as fast dynamic response, simple and robust control structure, direct torque control (DTC) is commonly used method in high performance control method for induction motors. Despite mentioned advantages, there are some chronically disadvantages with this method like high torque and current ripples, variable switching behaviour and control problems at low speed rates. On the other hand, artificial neural network (ANN) based control algorithms are getting increasingly popular in recent years due to their positive contribution to the system performance. The purpose of this paper is investigating of the effects of ANN integrated DTC method on induction motor performance by numerical simulations. For this purpose, two different ANN models have been designed, trained and implemented for the same DTC model. The first ANN model was designed to select optimum inverter and the second model was designed to use in the determination of the flux vector position. Matlab/Simulink model of the proposed ANN based DTC method was created in order to compare with the conventional DTC and the proposed DTC methods. The simulation studies proved that the induction motor torque ripples have been reduced remarkably with the proposed method and this approach can be a good alternative to the conventional DTC method for induction motor control.