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A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor

Author

Listed:
  • Lelisa Wogi

    (Department of Electrical and Computer Engineering, Bule Hora University, Bule Hora P.O. Box 144, Oromia, Ethiopia)

  • Tadele Ayana

    (Faculty of Electrical and Control Engineering, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland)

  • Marcin Morawiec

    (Faculty of Electrical and Control Engineering, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland)

  • Andrzej Jąderko

    (Faculty of Electrical Engineering, Czestochowa University of Technology, 42-201 Czestochowa, Poland)

Abstract

Multi-phase motors have recently replaced three-phase induction motors in a variety of applications due to the numerous benefits they provide, and the absence of speed sensors promotes induction motors with variable speed drives. Sensorless speed control minimizes unnecessary speed encoder cost, reduces maintenance, and improves the motor drive’s reliability. The performance comparison of the fuzzy sliding mode controller (FSMC) with adaptive fuzzy proportional integral derivative (AFPID) control methods for sensorless speed control of six-phase induction motors was analyzed in this study, and the proposed control system has an advantage for multiphase machines, specifically six-phase induction motors (IMs) in this study, as they are the current active research area for electric vehicles, hybrid electric vehicles, aerospace, ship propulsion, and high-power applications. The speed control of a six-phase induction motor was performed by using an AFPID controller and FSMC. The comparative performance analysis was based on sensorless speed control of the six-phase induction motor. A proportional integral derivative (PID) controller is commonly employed as it is used to eliminate oscillations, but it has several drawbacks, such as taking a long time to decrease the error and stabilize the system at constant speed. The fuzzy type-2 and PID controllers were hybridized so as to obtain the advantages of both to enhance the system performance. Finally, the comparison result revealed that the FSMC preforms significantly better by achieving good tracking performance. The control technique maintains the sliding mode approach’s robustness while providing reduced overshoots with a smooth control action, and the FSMC revealed good dynamic response under load variations when compared to the AFPID controller.

Suggested Citation

  • Lelisa Wogi & Tadele Ayana & Marcin Morawiec & Andrzej Jąderko, 2022. "A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor," Energies, MDPI, vol. 15(21), pages 1-29, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8183-:d:961258
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    References listed on IDEAS

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    1. S. Bououden & M. Chadli & H. R. Karimi, 2013. "Fuzzy Sliding Mode Controller Design Using Takagi-Sugeno Modelled Nonlinear Systems," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, February.
    2. Lina Wang & Haihui Zhang, 2018. "Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-6, December.
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    Cited by:

    1. Marwa Ben Slimene & Mohamed Arbi Khlifi, 2022. "Investigation on the Effects of Magnetic Saturation in Six-Phase Induction Machines with and without Cross Saturation of the Main Flux Path," Energies, MDPI, vol. 15(24), pages 1-18, December.
    2. Marcin Kaminski & Tomasz Tarczewski, 2023. "Neural Network Applications in Electrical Drives—Trends in Control, Estimation, Diagnostics, and Construction," Energies, MDPI, vol. 16(11), pages 1-25, May.

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