Intelligence hysteresis comparators for a multilevel DTC control scheme of IM drive

  • Habib Benbouhenni Ecole Nationale Polytechnique d'Oran Maurice Audin, Oran, Algeria
Keywords: DTC, IM, fuzzy logic, neural networks, five-level DTC.

Abstract

Direct torque control (DTC) of the induction motor (IM) is important in many applications. This paper presents improved five-level DTC using intelligence techniques. Two control approaches using neural networks DTC and fuzzy logic DTC are proposed and compared. The validity of the proposed controls scheme is verified by simulation tests of an induction motor. The stator current, stator flux and torque are determined and compared to the above techniques. The fuzzy DTC proposed control is shown to be able to reduce the torque and stator flux ripples and to improve performance DTC.

References

1. Kumar D., Thakur I., Gupta K., «Direct torque control for induction motor using intelligent artificial neural network technique, » International Journal of Energing Trends & Technonlogy in Computer Science, Vol. 3, No. 4, pp. 44-50, 2014.
2. Srihari T., Ieyabaharath R., Veena P., «ANFIS based space vector modulation-DTC for switched reluctance motor drive, » Circuits and Systems, Vol. 7, pp. 2940-2947, 2016.
3. Messaif I., EL-Madjid B., Saadi N., «A study of DTC-Power electronic cascade fed by photovoltaic cell-three-level NPC inverter, » Smart Grid and Renewable Energy, Vol. 1, pp. 109-118, 2010.
4. Benbouhenni H., « Comparateur à hystérésis à sept niveaux pour la commande DTC basée sur les techniques de l’intelligence artificielle de la MAS, » Journal of Advanced Research in Science and Technology, Vol. 4, No. 2, pp. 553-569, 2017.
5. Toufouti R., Meziane S., Benalla H., « Direct torque control for induction motor using intelligent techniques, » Journal of Theoretical and Applied Information Technology, 2007.
6. Douiri MY. R., Nasser T., Essadki A., Cherkaoui M., « Direct torque controle of induction motor based on artificial neural networks with estimate regulation speed using the MRAS and neural PI controller, » Journal of Theoretical and Applied Information Technology, 2010.
7. Messaoudi B., « Utilisation du contrôle directe du flux statorique et du filtre de kalman en vue du contrôle directe du couple d’un moteur asynchrone, » Mémoire de Magister, université Mohamed Khider de Biskra, 2007.
8. Bachwad M. R., Ashadeep M. M., «Study on topologies multilevel inverters, » International Journal of Engineering and Techniques, Vol. 1, No. 6, pp. 14-17, 2015.
9. Pavanajyothi G., Bhagya Lakashmi M., «Implementation of new PWM method for diode clamped multilevel inverter, » International Journal of Scientific Engineering and Applied Science, Vol. 1, No. 7, 2015.
10. Chibani R., Berkouk E. M., Boucherit M. S., « Five-level NPC-VSI capacitor voltage balancing using a novel clamping bridge, » Asian Power Electronics Journal, Vol. 5, No. 1, 2011.
11. Manivarma M., Suyuna J., Vimal Raj P., «Comparison of saven level inverter with reduced number of switches and their Thd’s in PI controller, » Journal of Electronics and Communication Engineering, pp. 32-42, 2016.
12. Benbouhenni, H., «Five-level DTC with 12 sectors of induction motor drive using neural networks controller for low torque ripple, » Acta Electrotechnica et Informatica, 18(2), pp. 61-66, 2018.
13. Abdelkrim T., Benamrane K., Benkhelifa Ach, Berkouk E. M., Benslimane T., «Five-level diode clamped active power filtre for high power utilities, » International Journal of Science and Techniques of Automatic Control & Computer Engineering, Vol. 5, No. 2, pp. 1634-1647, 2011.
14. Ameur A., Mokrani L., Mokhtari B., Essounbouli N., Azoui A., « Intelligent DTC of PMSM, fed by a three-phase NPC three-level inverter, » Acta Electrotehnica, Vol. 55, No. 1-2, 2014.
15. Benbouhenni, H., Zinelaabidine, B., Abdelkader, B., « Neuro-second order sliding mode control of a DFIG supplied by a two-level NSVM inverter for wind turbine system, » Iranian Journal of Electrical & Electronic Engineering, Vol. 14, No. 4, pp. 362-373, 2018.
16. Benbouhenni, H., « 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.
17. Idir A., Kidouche M., « Direct torque control of three phase induction motor drive using fuzzy logic controllers for low torque ripple, » Proceedings Engineering & Technology, Vol. 2, pp. 78-83, 2013.
18. El-Kholy E. E., Dabroom A. M., EL-Kholy Adef E. E., «Adaptive fuzzy logic controllers for DC drives: A survey of the state of the art, » Journal of Electrical Systems, Vol. 2, No. 3, pp. 116-145, 2006.
19. Benyoussef E., Meroufel A., Barkat S., «Three-level DTC based on fuzzy logic and neural network of sensorless DSSM using extende kalman filter, » International Journal of Power Electronics and Drive System (IJPEDS), Vol. 5, No. 4, pp. 453-463, 2015.
20. Balamurugan S., Vijaya Chandrakala K. R. M., Sankaramarayanan K., «Development of variable structure fuzzy logic controller for enhanced load frequency control, » Journal of Electrical Systems, Vol. 7, No. 3, pp. 297-307, 2011.
Published
2020-06-09
How to Cite
Benbouhenni, H. (2020). Intelligence hysteresis comparators for a multilevel DTC control scheme of IM drive. Majlesi Journal of Mechatronic Systems, 9(2). Retrieved from http://journals.iaumajlesi.ac.ir/ms/index/index.php/ms/article/view/414
Section
Articles

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