OICC Press Majlesi Journal of Electrical Engineering 2345-3796 4 4 2024 02 26 Forecasting PMLSM Direct Thrust Control Based on Neural Network by Considering Motors Dynamic Behavior and Speed Effects 10.1234/mjee.v4i4.300 EN Ghazanfar Shahgholian Department of Electronics Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran. Adel Deriszadeh Unknown Journal Article 2024 02 26 The direct thrust force control which is the direct torque control linear type method is modified in this article in order to eliminate the defects that are variable switching frequency and existing large ripples of force and flux, by keeping the advantages of thrust force control method which include simplicity of structure, low dependency to motor parameters and no requirement to coordination transformations. In previous works, the structure simplicity of DTC and low calculations, to reduce the force ripples and fixing switching frequency are disaffirmed, but with regards to keeping DTC advantages, a new method is presented in this article to eliminate the defects by the aid of neural network. for the first time, in this article, the precise non-linear behavior of PMLSM motor and effect of speed in voltage vectors selection in DTC has been considered by using space vector modulation and  it has been shown that despite considering motors non-linear behavior, the results concluded by the submitted intelligent DTC-SVM method, is more satisfactory than other methods