Forecasting PMLSM Direct Thrust Control Based on Neural Network by Considering Motors Dynamic Behavior and Speed Effects

The direct force thrust control (DTFC) is linear type of the direct torque control (DTC) method. The advantages of DTFC method are structure simplicity, low dependency to motor parameters and no requirement to coordination transformations. In this paper this method is modified in order to eliminate the defects that include the switching frequency and exciting large ripples of force and flux. In previous works, the structure simplicity of DTC, rare calculations to reduce the force ripples and fixing switching frequency are disaffirmed. With regards to keeping DTC advantages, a new method is presented in this paper to eliminate the defects by the aid of neural network. Also, the precise non-linear behavior of PMLSM motor in DTC has been considered by using space vector modulation. Finally, the simulation results concluded by the submitted intelligent DTC-SVM method are more satisfactory than other methods.