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A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks

Received: 23 February 2019    Accepted: 1 April 2019    Published: 26 April 2019
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Abstract

The direct torque control (DTC) is one of the actively researched control schemes of induction machines (IMs), which is based on the decoupled control of stator flux and electromagnetic torque. The traditional twelve sectors DTC control scheme of IM drive using hysteresis comparators and switching table has considerable electromagnetic torque ripple, stator flux ripple and harmonic distortion of voltage/current for IM drive. In order to ensure a robust twelve sectors DTC control scheme and minimize the harmonic distortion of stator current, a novel switching tables of twelve sectors DTC control scheme with the application of the artificial intelligence technique (artificial neural networks (ANNs)). The electromagnetic torque, stator flux and harmonic distortion of stator current are determined and compared with the traditional twelve sectors DTC control scheme. The simulation of the proposed switching tables were carried out in Matlab/Simulink software. A comparative study of the proposed switching tables is also presented to illustrate the merits of each of the switching table on the performance of the twelve sectors DTC control scheme.

Published in Automation, Control and Intelligent Systems (Volume 7, Issue 1)
DOI 10.11648/j.acis.20190701.11
Page(s) 1-8
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Direct Torque Control, Induction Motor, Neural Network, Twelve Sectors

References
[1] P. Rajasekaran, V. Jawahar Senthil Kumar, “An improved DTFC based five levels-NPC inverter fed induction motor for torque ripple minimization,” International Journal of Power Electronics and Drive System, Vol. 7, No. 2, pp. 531-542, 2016.
[2] H. Benbouhenni, Z. Boudjema, “Speed regulator and hysteresis based on artificial intelligence techniques of three-level DTC for induction motor,” Acta Electrotechnica et Informatica, Vol. 17 , No. 4, 2017, pp. 48-54.
[3] H. Benbouhenni,“36 Sectors DTC Based on Fuzzy Logic of Sensorless Induction Motor Drives,” Research & Reviews: Journal of Engineering and Technology, Vol. 7, No. 1, 2018, pp. 24-31.
[4] H. Benbouhenni, “Improved switching selection for DTC of induction motor drive using artificial neural networks,” Acta Electrotechnica et Informatica, Vol. 18, No. 1, pp.26-34, 2018.
[5] H. G. Zaini, M. K. Metwally, M. Ahmed, “Direct torque control of induction motor drive fed from hybrid multilevel inverter,” International Journal of Electrical & Computer Sciences, Vol. 14, No. 3, 2014.
[6] F. Benezzek, W. Bourbia, B. Bensaker, “Flatness based nonlinear sensorless control of induction motor systems,” International Journal of Power Electronics and Drive System, Vol. 7, No. 1, pp. 265-278, March 2016.
[7] H. Benbouhenni, “Five-level DTC with 12 sectors of induction motor drive using neural networks controller for low torque ripple,” Acta Electrotechnica et Informatica, Vol. 18, No. 2, pp. 61-66, 2018.
[8] V. Anantha Lakshni, V. C. Veera Reddy, M. Surya Kalavathi, “Direct torque control algorithm for induction motor drives for the mitigation of common mode voltage,” Innovation Systems Design and Engineering, Vol. 2, No. 4, 2011.
[9] H. Sudheer, SF. Kodad, B. Sarvesh, “Improved fuzzy logic based DTC of induction machine for wide range of speed control using AI based controllers,” Journal Electrical Systems, Vol. 12, No. 2, pp. 301-314, 2016.
[10] O. Benaouda, A. Bendiabdellah, “Comparative study of two types of DTC with application of artificial intelligence: Fuzzy logic and neuron network on the performance of a multi-level inverter feed induction machine,” International Journal of Research in Engineering & Technology, Vol. 2,No. 9, pp. 1-12, 2014.
[11] H. Benbouhenni, “24 sectors DTC control of IM drive using ANFIS controller for minimize torque ripple,” International Journal of Energy and Environment, Vol.12, pp. 24-29, 2018.
[12] H. Benbouhenni, “ Comparative study between neural hysteresis, fuzzy PI, and neural switching table for an IM DTC control,” International Journal of Fuzzy Systems and Advanced Applications, Vol. 5, pp. 23-34, 2018.
[13] B. Messaoudi, “Utilisation du controle directe du flux statorique et du filtre de Kalman en vue du controle directe du couple d’un moteur asynchrone,” Mémoire de Magister, université Mohamed Khider de Biskra, 2007.
[14] H. Benbouhenni, “ Six sectors DTC control of IM drives based on ANN with regulation speed using ANFIS controller,” ANNALS of Faculty Engineering Hunedoara – International Journal of Engineering, Vol. 16, No. 4, pp. 69-73, 2018.
[15] T. S. Ahmed, S. Sao, K. S. R. Aryaneyulu, “DTC of twelve sector IM drive using four level hysteresis control to reduce torque ripple comparing with conventional control,” International Journal of Engineering Research and Applications, Vol. 3, No. 1, pp. 115-120, 2013.
[16] A. H. Adel, S. Abo-Zaid, A. Refky, “Improvement of direct torque control of induction motor drives using Neuro-Fuzzy controller,” Journal of Multidisciplinary Engineering Science and Technology, Vol. 2, No. 10, 2015.
[17] F. Korkmaz, “Speed and Torque control of an induction motor with ANN based DTC,” International Journal of Instrumentation and Control Systemes (IJICS), Vol. 7, No. 1, 2017.
[18] H. Benbouhenni, “Seven-level direct torque control of induction motor based on artificial neural networks with regulation speed using fuzzy PI controller,” Iranian Journal of Electrical and Electronic Engineering, Vol. 14, No. 1, pp. 85-94, 2018.
[19] H. Benbouhenni, “Four-level DTC with six sectors based on neural network of induction motor,” Journal Acta Electrotehnica, Vol. 58, No. 4, pp. 293-300, 2018 .
[20] H. Benbouhenni, “ANFIS speed controller of IM drives with three-level DTC-based neural network,” Majlesi Journal of Mechatronic Systems, Vol. 8, No. 1, 2019.
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  • APA Style

    Habib Benbouhenni. (2019). A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks. Automation, Control and Intelligent Systems, 7(1), 1-8. https://doi.org/10.11648/j.acis.20190701.11

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    ACS Style

    Habib Benbouhenni. A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks. Autom. Control Intell. Syst. 2019, 7(1), 1-8. doi: 10.11648/j.acis.20190701.11

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    AMA Style

    Habib Benbouhenni. A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks. Autom Control Intell Syst. 2019;7(1):1-8. doi: 10.11648/j.acis.20190701.11

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  • @article{10.11648/j.acis.20190701.11,
      author = {Habib Benbouhenni},
      title = {A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks},
      journal = {Automation, Control and Intelligent Systems},
      volume = {7},
      number = {1},
      pages = {1-8},
      doi = {10.11648/j.acis.20190701.11},
      url = {https://doi.org/10.11648/j.acis.20190701.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20190701.11},
      abstract = {The direct torque control (DTC) is one of the actively researched control schemes of induction machines (IMs), which is based on the decoupled control of stator flux and electromagnetic torque. The traditional twelve sectors DTC control scheme of IM drive using hysteresis comparators and switching table has considerable electromagnetic torque ripple, stator flux ripple and harmonic distortion of voltage/current for IM drive. In order to ensure a robust twelve sectors DTC control scheme and minimize the harmonic distortion of stator current, a novel switching tables of twelve sectors DTC control scheme with the application of the artificial intelligence technique (artificial neural networks (ANNs)). The electromagnetic torque, stator flux and harmonic distortion of stator current are determined and compared with the traditional twelve sectors DTC control scheme. The simulation of the proposed switching tables were carried out in Matlab/Simulink software. A comparative study of the proposed switching tables is also presented to illustrate the merits of each of the switching table on the performance of the twelve sectors DTC control scheme.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - A Novel Switching Tables of Twelve Sectors DTC for Induction Machine Drive Using Artificial Neural Networks
    AU  - Habib Benbouhenni
    Y1  - 2019/04/26
    PY  - 2019
    N1  - https://doi.org/10.11648/j.acis.20190701.11
    DO  - 10.11648/j.acis.20190701.11
    T2  - Automation, Control and Intelligent Systems
    JF  - Automation, Control and Intelligent Systems
    JO  - Automation, Control and Intelligent Systems
    SP  - 1
    EP  - 8
    PB  - Science Publishing Group
    SN  - 2328-5591
    UR  - https://doi.org/10.11648/j.acis.20190701.11
    AB  - The direct torque control (DTC) is one of the actively researched control schemes of induction machines (IMs), which is based on the decoupled control of stator flux and electromagnetic torque. The traditional twelve sectors DTC control scheme of IM drive using hysteresis comparators and switching table has considerable electromagnetic torque ripple, stator flux ripple and harmonic distortion of voltage/current for IM drive. In order to ensure a robust twelve sectors DTC control scheme and minimize the harmonic distortion of stator current, a novel switching tables of twelve sectors DTC control scheme with the application of the artificial intelligence technique (artificial neural networks (ANNs)). The electromagnetic torque, stator flux and harmonic distortion of stator current are determined and compared with the traditional twelve sectors DTC control scheme. The simulation of the proposed switching tables were carried out in Matlab/Simulink software. A comparative study of the proposed switching tables is also presented to illustrate the merits of each of the switching table on the performance of the twelve sectors DTC control scheme.
    VL  - 7
    IS  - 1
    ER  - 

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Author Information
  • Electrical Engineering Department, National Polytechnique School of Oran Maurice Audin, LAAS Research Laboratory, Oran, Algeria

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