Comparative study of ANN DTC and conventional DTC controlled PMSM motor

A. Ghamri, R. Boumaaraf, M.T. Benchouia, H. Mesloub, A. Goléa and N. Goléa

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 167, issue C, 219-230

Abstract: In this paper an Artificial Neural Network (ANN) algorithm is presented in order to solve the problems associated with the conventional DTC approach. In order to improve the performances of the DTC controlled PMSM and to reject the disturbances, an ANN algorithm is used. This intelligent artificial technique is used to select the optimal voltage vector. In order to reduce the torque and flux ripples, the hysteresis comparators and the switching table have been substituted by the ANN technique. Simulation using Matlab/Simulink environment and experimental results around the Dspace-1104, are presented to test the performances of this approach. Simulation and experimental results show the high performances of the ANN-DTC compared to the conventional DTC; in particular the reduction of the ripples in torque and flux.

Keywords: Permanent magnet synchronous motor (PMSM); Direct torque control (DTC); Artificial neural networks (ANN) (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:167:y:2020:i:c:p:219-230

DOI: 10.1016/j.matcom.2019.09.006

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