ANFIS Speed Controller of IM Drives with Three-level DTC-based Neural Network
Keywords:
ANFIS, DTC, Induction machine
Abstract
Direct torque control (DTC) is a control technique in AC drive systems to obtain high-performance torque control. In this paper, we use a technique based on the neural network and ANFIS controller in order to reduce the torque ripple, stator flux ripple and THD value of stator current in the induction machine (IM). The effect is highlighted by considering the machine controlled by the 24 sectors DTC. In this paper, we propose to replace conventional selector states of switches inverter by a neural selector able to generate the same signals to control this inverter, on the other hand, the classic PI controller of speed is proposed based on Adaptive Neuro Fuzzy Inference System (ANFIS) controller. Simulation results are presented and show the effectiveness of the proposed control scheme.
References
[1] D. C. Sekhar, G. V. Marutheshwar, “Modeling and field oriented control of induction motor by using an adaptive neuro fuzzy interference system control technique,” International Journal of Industriel Electronics and Electrical Engineering, Vol. 2, No. 10, 2014, pp. 75-81.
[2] D. C. Sekhar, G. V. Marutheshwar, “Modeling and direct torque control of induction motor by using hybrid control technique,” Electrical and Electronics Engineering: An International Journal, Vol. 3, No. 2, 2014, pp. 17-33.
[3] A. D. Bhavani, G. D. Devi, K. Satyanarayana, “An improved speed and torque performance of ANFIS based direct torque controlled induction motor drive,” International Journal of Scientific & Engineering Research, Vol. 6, Issue 12, 2015, pp. 323-327.
[4] A. Miloudi, E. A. AL-Radadi, A. D. Draou, “A variable gain PI controller of a direct torque neuro fuzzy controlled induction machine drive,” Turk. J. Elec. Engin, Vol. 15, No. 1, 2007, pp. 37-49.
[5] T. Srihari, R. Jeyabaharath, P. Veena, “ANFIS based space vector modulation DTC for switched reluctance motor drive,” Circuits and Systems, Vol. 7, 2016, pp. 2940-2947.
[6] B. Mokhtari, A. Ameur, M. F. Benkhoris, L. Mokrani, B. Azoui, “Experimental DTC of an induction motor Applied to optimize a tracking system,” International Conference on Renewable Energies and Power Quality (ICREPQ’12), 28th too 30th March, Santiago de Compostela (Spain), 2012.
[7] H. Benbouhenni, “Comparateur à hysteresis 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, 2017, pp. 553-569.
[8] S. B. Kadu, J. G. Choudhari, “Comparision between two levels and three level inverter for direct torque control induction motor drive,” Journal of Electrical and Electronics Engineering, 2014, pp. 72-79.
[9] S. Darwin, M. Murugan, J. J. Gnana Chandran, “A comparative interestigation on DTC of B4-inverter-fed BLDC motor drives using PI and intelligent controllers,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4, No. 3, 2015, pp. 1486-1494.
[10] E. Benyoussef, A. Meroufel, S. Barakat, “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, Vol. 5, No. 4, 2015, pp. 453-463.
[11] H. Benbouhenni, R. Taleb, “ Nouveaux tableaux de commutations de la commande DTC d’une MAS alimentée par onduleur NPC à trois niveaux,” 4ème Conférence Internationale des Energies Renouvelables (CIER-2016) Hammamet – Tunisie, Décembre 20 - 22, 2016.
[12] F. Kadri, S. Drid, F. Djeffal, “ Direct torque control of induction motor fed by three-level NPC inverter using fuzzy logic,” International Conference on Systems and Processing Information, May 15-17, 2011, Guelma, Algeria.
[13] E. Benyoussef, A. Meroufel, S. Barakat, “Multilevel direct torque balancing control of double star synchronous machine,” Journal of Electrical Engineering, Vol. 14, No. 4, 2014, pp. 1-11.
[14] Y. B. Goswami, S. M. Deshmukh, “Adaptive neuro fuzzy inference based direct torque control strategy for robust speed control of induction motor under highly variable load conditions,” International Journal of Science and Research, Vol. 14, No. 12, 2015, pp. 1273-1277.
[15] D. Narasimha Rao, T. Surendra, S. Tara Kalyani, “DPFC performance with the comparison of PI and ANN controller,” International Journal of Electrical and Computer Engineering, Vol. 6, No. 5, 2016, pp. 2080-2087.
[16] 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, 2018, pp. 85-94 .
[17] D. D. Micu, L. Czumbil, G. Christoforids, E. Simion, “Neural networks applied in Electromagnetic inference problems,” Rev. Roum, Sci. Techn.-Electrotechn. Et Energ, Vol. 57, No. 2, 2012, pp. 162-171.
[2] D. C. Sekhar, G. V. Marutheshwar, “Modeling and direct torque control of induction motor by using hybrid control technique,” Electrical and Electronics Engineering: An International Journal, Vol. 3, No. 2, 2014, pp. 17-33.
[3] A. D. Bhavani, G. D. Devi, K. Satyanarayana, “An improved speed and torque performance of ANFIS based direct torque controlled induction motor drive,” International Journal of Scientific & Engineering Research, Vol. 6, Issue 12, 2015, pp. 323-327.
[4] A. Miloudi, E. A. AL-Radadi, A. D. Draou, “A variable gain PI controller of a direct torque neuro fuzzy controlled induction machine drive,” Turk. J. Elec. Engin, Vol. 15, No. 1, 2007, pp. 37-49.
[5] T. Srihari, R. Jeyabaharath, P. Veena, “ANFIS based space vector modulation DTC for switched reluctance motor drive,” Circuits and Systems, Vol. 7, 2016, pp. 2940-2947.
[6] B. Mokhtari, A. Ameur, M. F. Benkhoris, L. Mokrani, B. Azoui, “Experimental DTC of an induction motor Applied to optimize a tracking system,” International Conference on Renewable Energies and Power Quality (ICREPQ’12), 28th too 30th March, Santiago de Compostela (Spain), 2012.
[7] H. Benbouhenni, “Comparateur à hysteresis 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, 2017, pp. 553-569.
[8] S. B. Kadu, J. G. Choudhari, “Comparision between two levels and three level inverter for direct torque control induction motor drive,” Journal of Electrical and Electronics Engineering, 2014, pp. 72-79.
[9] S. Darwin, M. Murugan, J. J. Gnana Chandran, “A comparative interestigation on DTC of B4-inverter-fed BLDC motor drives using PI and intelligent controllers,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4, No. 3, 2015, pp. 1486-1494.
[10] E. Benyoussef, A. Meroufel, S. Barakat, “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, Vol. 5, No. 4, 2015, pp. 453-463.
[11] H. Benbouhenni, R. Taleb, “ Nouveaux tableaux de commutations de la commande DTC d’une MAS alimentée par onduleur NPC à trois niveaux,” 4ème Conférence Internationale des Energies Renouvelables (CIER-2016) Hammamet – Tunisie, Décembre 20 - 22, 2016.
[12] F. Kadri, S. Drid, F. Djeffal, “ Direct torque control of induction motor fed by three-level NPC inverter using fuzzy logic,” International Conference on Systems and Processing Information, May 15-17, 2011, Guelma, Algeria.
[13] E. Benyoussef, A. Meroufel, S. Barakat, “Multilevel direct torque balancing control of double star synchronous machine,” Journal of Electrical Engineering, Vol. 14, No. 4, 2014, pp. 1-11.
[14] Y. B. Goswami, S. M. Deshmukh, “Adaptive neuro fuzzy inference based direct torque control strategy for robust speed control of induction motor under highly variable load conditions,” International Journal of Science and Research, Vol. 14, No. 12, 2015, pp. 1273-1277.
[15] D. Narasimha Rao, T. Surendra, S. Tara Kalyani, “DPFC performance with the comparison of PI and ANN controller,” International Journal of Electrical and Computer Engineering, Vol. 6, No. 5, 2016, pp. 2080-2087.
[16] 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, 2018, pp. 85-94 .
[17] D. D. Micu, L. Czumbil, G. Christoforids, E. Simion, “Neural networks applied in Electromagnetic inference problems,” Rev. Roum, Sci. Techn.-Electrotechn. Et Energ, Vol. 57, No. 2, 2012, pp. 162-171.
Published
2019-02-15
How to Cite
Benbouhenni, H. (2019). ANFIS Speed Controller of IM Drives with Three-level DTC-based Neural Network. Majlesi Journal of Mechatronic Systems, 8(1), 11-17. Retrieved from https://ms.majlesi.info/index.php/ms/article/view/387
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