Abstract
Nowadays, thanks to the development of control and power electronics, the dual stator induction machine DSIM has become among the most important multi-phase machines included in industrial application, this is due to its positive features among them is its high reliability and reduce both losses and rotor torque ripple.
This paper aims to apply both techniques of artificial intelligence represented by the neural network algorithm NNA and the Space Vector PWM SVM for direct torque control DTC of the DSIM to improve the machine performance and control algorithms DTNC and DTC-SVM.
Generalization capacity, the parallelism of operation, computational speed, and learning capacity all these features made it possible to exploit the neural network algorithm to control the machine. Fixed switching frequency obtained, dispensed with the vector selection table and the hysteresis controller, the three pros allowed the inclusion of SVM technique in DTC strategy.
Three-level NPC inverters are included to feed the DSIM. A several of the results obtained prove the two applied techniques (NNA, SVPWM) in improving the quality of both electromagnetic torque and flux and the dynamic responses of the DSIM.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Duran, M.J., Gonzalez-Prieto, I., Rios-Garcia, N., Barrero, F.: A simple fast and robust open-phase fault detection technique for six-phase induction motor drives. IEEE Trans. Power Electron. 33(1), 547–557 (2018)
Levi, E.: Multiphase electric machines for variable-speed applications. IEEE Trans. Industr. Electron. 55(5), 1893–1909 (2008)
Basak, S., Chakraborty, C.: Dual stator winding induction machine: problems, progress, and future scope. IEEE Trans. Industr. Electron. 62(7), 4641–4652 (2015)
Kianinezhad, R., Nahid, B., Baghi, L., Betin, F., Capolino, G.A.: Modeling and control of six-phase symmetrical induction machine under fault condition due to open phases. IEEE Trans. Ind. Appl. 55(5), 1966–1977 (2008)
Talaeizadeh, V., Kianinezhad, R., Seyfossadat, S.G., Shayanfar, H.A.: Direct torque control of six-phase induction motors using three-phase matrix converter. Energy Convers. Manag. 51, 2482–2491 (2010)
Zhao, Y., Lipo, T.A.: Space vector PWM control of dual three-phase induction machine using vector space decomposition. IEEE Trans Ind Appl 31(5), 1100–1109 (1995)
Benaouda, O.F., Bendiabdellah, A., Cherif, B.D.E.: Contribution to reconfigured multi-level inverter fed double stator induction machine DTC-SVM control. Int. Rev. Modell. Simul. 9(5), 1–12 (2016)
Bojoi, R., Farina, F., Griva, G., Profumo, F., Tenconi, A.: Direct torque control for dual three-phase induction motor drives. IEEE Trans. Ind. Appl. 41(6), 1627–1636 (2005)
Benaouda, O.F., Babess, B., Bouchakour, M., Kahla, S., Bendiabdellah, A.: Arc welding current Control using thyristor based three-phase rectifiers applied to gas metal arc welding connected to grid network. J. Eur. Syst. Autom. 54(2), 335–344 (2021)
Benaouda, O.F., Bendiabdellah, A., Kahla, S.: Contribution to reconfiguration of fault-tolerant inverter applied to the wind park connected to the electrical network. Int. Rev. Modell. Simul. 9(5) (2016). pp. 143–148, Bucarest (2019)
Ben Abdelghani, H., Ben Abdelghani, A.B., Belkhodja, I.S.: Three-level fault-tolerant DTC control for induction machine drives. In: 9th IEEE Annual System and Devices. Special Conference, pp. 1–6, March 2012
Krim, S., Gdaim, S., Mtibaa, A., Mimouni, M.F.: Real time implementation of high performance’s direct torque control of induction motor on FPGA. Int. Rev. Electr. Eng. (IREE) 9(5), 919–929 (2014)
Casadei, D., Profumo, F., Serra, G., Tani, A.: FOC and DTC: two viable schemes for induction motors torque control. IEEE Trans. Power Electron. 17(5), 779–787 (2002)
Toufouti, R.: Contribution à la Commande Direct du Couple de la Machine Asynchrone, (Contribution to the Direct Torque Control of the Induction Machine). PhD Thesis, Mantoury University Constantine, Algeria (2008)
Acknowledgment
This work was supported by Research Center in Industrial Technologies CRTI, P.O.Box 64, Cheraga 16014, Algiers, Algeria crti.dz.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Benaouda, O.F., Mezaache, M., Abdelkader, R., Bendiabdellah, A. (2022). A Comparative Study Between the Two Applications of the Neural Network and Space Vector PWM for Direct Torque Control of a DSIM Fed by Multi-level Inverters. In: Lejdel, B., Clementini, E., Alarabi, L. (eds) Artificial Intelligence and Its Applications. AIAP 2021. Lecture Notes in Networks and Systems, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-96311-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-96311-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96310-1
Online ISBN: 978-3-030-96311-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)