Artificial neural network sensorless direct torque control of two parallel-connected five-phase induction machines

Majlesi Journal of Electrical Engineering

دوره 18، شماره 3، آذر 2024، صفحه 1-14   

نوع مقاله: Reseach Article

شناسه دیجیتال (DOI): 10.57647/j.mjee.2024.180348

چکیده

Conventional direct torque control (DTC) improves the dynamic performance of the five-phase induction machine (FPIM). Nevertheless, it suffers from significant drawbacks of high stator flux and electromagnetic torque ripples. Moreover, the DTC technique relies on an open-loop estimator for accurate stator flux module and position knowledge. However, this method is subjected to substandard performance, mainly during the low-speed operation range. Therefore, a sliding mode sensorless stator flux and rotor speed DTC based on an artificial neural network (DTC-ANN) for two parallel-connected FPIMs is discussed to tackle the problems above. This approach optimizes the DTC performance by replacing the two hysteresis controllers (HC) and the look-up table. As for the poor estimation drawback, the sliding mode observer (SMO) offers a robust estimation and reconstruction of the FPIM variables and eliminates the need for additional sensors, increasing the system’s reliability. The present results verify and compare the performance of the control scheme.

کلیدواژه‌ها

Five-phase induction motor (FPIM)؛ Direct torque control (DTC)؛ Artificial neural network (ANN)؛ Parallelconnected two-motor drive؛ Sensorless control؛ Sliding mode observer (SMO)

مراجع

[1] M. Bermudez et al. “An experimental assessment of open-phase fault-tolerant virtual-vectorbased direct torque control in five-phase induction motor drives.”. IEEE Transactions on Power
Electronics, 33(3):pp. 2774–2784, 2018. DOI:
https://doi.org/10.1109/tpel.2017.2711531.
[2] S. Guedida et al. “Direct torque control scheme
for less harmonic currents and torque ripples
for dual star induction motor.”. Revue Roumaine
des Sciences Techniques, Serie ´ Electrotechnique ´
et Energ ´ etique ´ , 68(4):pp. 331–338, 2023. DOI:
https://doi.org/10.59277/RRST-EE.2023.4.2.
[3] E. Levi. “Multiphase electric machines for variablespeed applications.”. IEEE Transactions on Industrial Electronics, 55(5):pp. 1893–1909, 2008. DOI:
https://doi.org/10.1109/tie.2008.918488.
[4] S. Payami, R. K. Behera, and A. Iqbal. “DTC
of three-level NPC inverter fed five-phase induction motor drive with novel neutral point voltage balancing scheme.”. IEEE Transactions on
Power Electronics, 33(2):pp. 1487–1500, 2018. DOI:
https://doi.org/10.1109/tpel.2017.2675621.
[5] Y. N. Tatte and M. V. Aware. “Torque ripple
and harmonic current reduction in a three-level
inverter-fed direct-torque-controlled five-phase induction motor.”. IEEE Transactions on Industrial Electronics, 64(7):pp. 5265–5275, 2017. DOI:
https://doi.org/10.1109/tie.2017.2677346.
[6] S. Mahfoud et al. “Enhancement of the direct
torque control by using artificial neuron network for a doubly fed induction motor.”. Intelligent Systems with Applications, 13, 2022. DOI:
https://doi.org/10.1016/j.iswa.2022.200060.
[7] S. Gdaim, A. Mtibaa, and M. F. Mimouni. “Artificial
Neural Network-based DTC of an induction
machine with experimental implementation on
FPGA.”. Engineering Applications of Artificial Intelligence, 121:pp. 105972, 2023. DOI:
https://doi.org/10.1016/j.engappai.2023.105972.
[8] A. Ghamri et al. “Comparative study of
ANN DTC and conventional DTC controlled
PMSM Motor.”. Mathematics and Computers
in Simulation, 167:pp. 219–230, 2020. DOI:
https://doi.org/10.1016/j.matcom.2019.09.006.
[9] R. Araria, K. Negadi, and F. Marignetti. “Design
and analysis of the speed and torque control of Im
with DTC based Ann Strategy for Electric Vehicle
Application. ”. TECNICA ITALIANA-Italian Journal
of Engineering Science, 63(2-4):pp. 181–188, 2019.
DOI: https://doi.org/10.18280/ti-ijes.632-410.
[10] 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, 14(1):pp. 85–94, 2018. DOI:
https://doi.org/10.22068/IJEEE.14.1.85.
[11] R. Kumar et al. “Artificial neural network
based direct torque control of induction motor
drives.”. IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES), :361–367, 2007. DOI:
https://doi.org/10.1049/ic:20070638.
[12] A. Zemmit, S. Messalti, and A. Harrag. “Innovative
improved Direct Torque Control of Doubly Fed
Induction Machine (DFIM) using Artificial Neural
Network (ANN-DTC).”. International Journal of
Applied Engineering Research, 11(16):pp. 9099–9105,
2016.
[13] Y. N. Tatte et al. “Performance improvement of
three-level five-phase inverter-fed DTC-controlled
five-phase induction motor during low-speed operation.”. IEEE Transactions on Industry Applications, 54(3):pp. 2349–2357, 2018. DOI:
https://doi.org/10.1109/tia.2018.2798593.
[14] R. Inan. “A novel fpga-based BI input-reduced order extended Kalman filter for speed-sensorless
direct torque control of induction motor with constant switching frequency controller.”. IET Computers & amp; Digital Techniques, 15(3):pp. 185–201,
2021. DOI: https://doi.org/10.1049/cdt2.12011.
[15] T. Kamel et al. “Extended Kalman filter based sliding mode control of parallel-connected two fivephase PMSM Drive System.”. Electronics, 7(2):pp.
14, 2018. URL 10.3390/electronics7020014.
[16] E. Zerdali and M. Barut. “Extended Kalman filter
based speed-sensorless load torque and inertia estimations with observability analysis for Induction
Motors.”. Power Electronics and Drives, 3(1):pp.
115–127, 2018. DOI: https://doi.org/10.2478/pead2018-0002.
[17] S. Guedida et al. “Novel speed sensorless DTC design for a five-phase induction motor with an intelligent fractional order controller based-mras estimator.”. Power Electronics and Drives, 9(1):pp. 63–85,
2024. DOI: https://doi.org/10.2478/pead-2024-0005.
[18] S. Jnayah and A. Khedher. “Sensorless direct torque
control of induction motor using Sliding mode flux
observer.”. 19th International Conference on Sciences
and Techniques of Automatic Control and Computer
Engineering (STA), page pp. 536–541, 2019. DOI:
https://doi.org/10.1109/sta.2019.8717270.
[19] Y. Zhang et al. “A comparative study of Luenberger
Observer, sliding mode observer and extended
Kalman filter for sensorless vector control of induction motor drives.”. IEEE Energy Conversion
Congress and Exposition, page pp. 2466–2473, 2009.
DOI: https://doi.org/10.1109/ecce.2009.5316508.[20] A. Ammar, A. Bourek, and A. Benakcha. “Sensorless
SVM-direct torque control for Induction Motor
Drive using sliding mode observers.”. Journal of
Control, Automation and Electrical Systems, 28(2):pp.
189–202, 2016. DOI: https://doi.org/10.1007/s40313-
016-0294-7.
[21] K. M. S. Benzaoui, E. Benyoussef, and A. Z.
Kouache. “Three-level direct torque control based
on common mode voltage reduction strategy FED
Two parallel connected Five-Phase induction machine.”. Revue Roumaine DES Sciences TechniquesSerie ´ Electrotechnique et ´ Energ ´ etique ´ , 69(2):pp.
177–182, 2024. DOI: https://doi.org/10.59277/RRSTEE.2024.69.2.10.
[22] M. Bermudez et al. “Open-phase fault-tolerant
direct torque control technique for five-phase induction motor drives.”. IEEE Transactions on Industrial Electronics, 64(2):pp. 902–911, 2017. DOI:
https://doi.org/10.1109/tie.2016.2610941.
[23] O. Saadeh, M. Dalbah, and Z. Dalala. “Control of two
five-phase parallel connected single source motor
drives under balanced and unbalanced conditions.”.
9th IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 2018.
DOI: https://doi.org/10.1109/pedg.2018.8447807.
[24] A. Bıc¸ak and A. Gelen. “Sensorless Direct Torque
Control based on seven-level torque hysteresis controller for five-phase IPMSM using a sliding-mode
observer.”. Engineering Science and Technology, an
International Journal, 24(5):pp. 1134–1143, 2021.
DOI: https://doi.org/10.1016/j.jestch.2021.02.004.
[25] M. Ghanes. “Observation et commande de la machine asynchrone sans capteur mecanique ´ .”. These `
de doctorat, 2005.
[26] F. Mehazzem. “Contribution a la commande `
d’un moteur asynchrone destine´ a la traction `
electrique ´ .”. These de doctorat ` , 2010.