Direct Torque Control of Induction Motor Based on Artificial Neural Networks with Estimate and Regulation Speed Using the Mras and Neural Pi Controller

This paper presents an improved direct torque of induction machine based on artificial neural networks. This intelligent technique was used to replace, on the one hand the conventional comparators and the selection table in order to reduce torque ripple, flux and stator current, on the other hand and the classic integral proportional (PI) in order to increase the response time period of the system, to optimize the performances of the closed loop control, and to adjust the parameters of the regulator to changes in the reference level. Then we estimated the rotor speed using the Model Reference Adaptive Control “MRAS” method based on measurements of electrical quantities of the machine. The validity of the proposed methods is confirmed by the simulation results.