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High –Performance using Neural Networks in Direct Torque Control for Asynchronous Machine

Mekrini, ZinebBri, Seddik
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 April 2018
DOI10.11591/ijece.v8i2.pp1010-1017

Abstrak

This article investigates solution for the biggest problem of the Direct Torque Control on the asynchronous machine to have the high dynamic performance with very simple hysteresis control scheme. The Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, as well as flux control at very low speed. In this paper, we propose an intelligent approach to improve the direct torque control of induction machine which is an artificial neural networks control. The principle, the numerical procedure and the performances of this method are presented.  Simulations results show that the proposed ANN-DTC strategy effectively reduces the torque and flux ripples at low switching frequency, compared with Fuzzy Logic DTC and The Conventional DTC.

Kata Kunci

Asynchronous MachineArtificial neural networksTorque rippleFlux rippleElectromagnetic flux

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High –Performance using Neural Networks in Direct Torque Control for Asynchronous Machine | International Journal of Electrical and Computer Engineering (IJECE) | Publiora