IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i7p2689-d787924.html
   My bibliography  Save this article

A Comparative Study and Optimization of Switching Functions for Sliding-Mode Observer in Sensorless Control of PMSM

Author

Listed:
  • Karol Kyslan

    (Department of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Viktor Petro

    (Department of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Peter Bober

    (Department of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Viktor Šlapák

    (Department of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • František Ďurovský

    (Department of Electrical Engineering and Mechatronics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Mateusz Dybkowski

    (Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Matúš Hric

    (SPINEA Technologies Ltd., 080 01 Prešov, Slovakia)

Abstract

The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its high reliability, economic and safety benefits. A fast and high-precision rotor-position estimation is inevitable for the implementation of sensorless control. Sliding-mode observer (SMO) is a preferred solution for sensorless control by many industrial companies. This article addresses the comparison of different switching functions employed in the control structure of sensorless field-oriented control with SMO. The switching functions are classified and their influence on the performance of the PMSM is verified for different shaping coefficients (SC). In addition, a statistical evaluation of the switching functions is provided to find the optimal values of SC. An experimental and statistical evaluation validated the substitutability of signum and hyperbolic switching functions and optimal values of SC have been found.

Suggested Citation

  • Karol Kyslan & Viktor Petro & Peter Bober & Viktor Šlapák & František Ďurovský & Mateusz Dybkowski & Matúš Hric, 2022. "A Comparative Study and Optimization of Switching Functions for Sliding-Mode Observer in Sensorless Control of PMSM," Energies, MDPI, vol. 15(7), pages 1-17, April.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2689-:d:787924
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/7/2689/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/7/2689/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ming-Shyan Wang & Tse-Ming Tsai, 2017. "Sliding Mode and Neural Network Control of Sensorless PMSM Controlled System for Power Consumption and Performance Improvement," Energies, MDPI, vol. 10(11), pages 1-15, November.
    2. Justas Dilys & Voitech Stankevič & Krzysztof Łuksza, 2021. "Implementation of Extended Kalman Filter with Optimized Execution Time for Sensorless Control of a PMSM Using ARM Cortex-M3 Microcontroller," Energies, MDPI, vol. 14(12), pages 1-16, June.
    3. Danyang Bao & Huiming Wu & Ruiqi Wang & Fei Zhao & Xuewei Pan, 2020. "Full-Order Sliding Mode Observer Based on Synchronous Frequency Tracking Filter for High-Speed Interior PMSM Sensorless Drives," Energies, MDPI, vol. 13(24), pages 1-19, December.
    4. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alessandro Benevieri & Lorenzo Carbone & Simone Cosso & Krishneel Kumar & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2022. "Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review," Energies, MDPI, vol. 15(20), pages 1-26, October.
    2. Shu Xiong & Jian Pan & Yucui Yang, 2022. "Robust Decoupling Vector Control of Interior Permanent Magnet Synchronous Motor Used in Electric Vehicles with Reduced Parameter Mismatch Impacts," Sustainability, MDPI, vol. 14(19), pages 1-16, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pawel Latosinski & Andrzej Bartoszewicz, 2023. "Sliding Mode Controllers in Energy Systems and Other Applications," Energies, MDPI, vol. 16(3), pages 1-4, January.
    2. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    3. Shuai Li & Ke Zhu & Liang Chen & Yao Yan & Qing Guo, 2022. "Variable Structure Disturbance Observer Based Dynamic Surface Control of Electrohydraulic Systems with Parametric Uncertainty," Energies, MDPI, vol. 15(5), pages 1-15, February.
    4. Lorenzo Carbone & Simone Cosso & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2021. "State-Space Approach for SPMSM Sensorless Passive Algorithm Tuning," Energies, MDPI, vol. 14(21), pages 1-11, November.
    5. Christian Aldrete-Maldonado & Ramon Ramirez-Villalobos & Luis N. Coria & Corina Plata-Ante, 2023. "Sensorless Scheme for Permanent-Magnet Synchronous Motors Susceptible to Time-Varying Load Torques," Mathematics, MDPI, vol. 11(14), pages 1-20, July.
    6. Yujiao Zhao & Haisheng Yu & Shixian Wang, 2021. "An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 14(19), pages 1-18, September.
    7. Alessandro Benevieri & Lorenzo Carbone & Simone Cosso & Krishneel Kumar & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2022. "Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review," Energies, MDPI, vol. 15(20), pages 1-26, October.
    8. Nikola Lopac & Neven Bulic & Niksa Vrkic, 2019. "Sliding Mode Observer-Based Load Angle Estimation for Salient-Pole Wound Rotor Synchronous Generators," Energies, MDPI, vol. 12(9), pages 1-22, April.
    9. Jongwon Choi & Kwanghee Nam, 2018. "Wound Synchronous Machine Sensorless Control Based on Signal Injection into the Rotor Winding," Energies, MDPI, vol. 11(12), pages 1-20, November.
    10. Shuo Chen & Xiao Zhang & Xiang Wu & Guojun Tan & Xianchao Chen, 2019. "Sensorless Control for IPMSM Based on Adaptive Super-Twisting Sliding-Mode Observer and Improved Phase-Locked Loop," Energies, MDPI, vol. 12(7), pages 1-19, March.
    11. Claudiu-Ionel Nicola & Marcel Nicola, 2023. "Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    12. Weidong Feng & Jing Bai & Zhiqiang Zhang & Jing Zhang, 2022. "A Composite Variable Structure PI Controller for Sensorless Speed Control Systems of IPMSM," Energies, MDPI, vol. 15(21), pages 1-18, November.
    13. Xiaofei Zhang & Hongbin Ma, 2019. "Data-Driven Model-Free Adaptive Control Based on Error Minimized Regularized Online Sequential Extreme Learning Machine," Energies, MDPI, vol. 12(17), pages 1-17, August.
    14. Habib Benbouhenni & Nicu Bizon, 2021. "Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems," Energies, MDPI, vol. 14(18), pages 1-20, September.
    15. Artun Sel & Bilgehan Sel & Umit Coskun & Cosku Kasnakoglu, 2022. "SOS-Based Nonlinear Observer Design for Simultaneous State and Disturbance Estimation Designed for a PMSM Model," Sustainability, MDPI, vol. 14(17), pages 1-12, August.
    16. Thyago Estrabis & Gabriel Gentil & Raymundo Cordero, 2021. "Development of a Resolver-to-Digital Converter Based on Second-Order Difference Generalized Predictive Control," Energies, MDPI, vol. 14(2), pages 1-22, January.
    17. Yang Cao & Jian Guo, 2022. "Sensorless Control of High-Speed Motors Subject to Iron Loss," Energies, MDPI, vol. 15(20), pages 1-14, October.
    18. Omer Cihan Kivanc & Salih Baris Ozturk, 2019. "Low-Cost Position Sensorless Speed Control of PMSM Drive Using Four-Switch Inverter," Energies, MDPI, vol. 12(4), pages 1-24, February.
    19. Quntao An & Yuzhuo Lu & Mengji Zhao, 2024. "Review of Key Technologies of the High-Speed Permanent Magnet Motor Drive," Energies, MDPI, vol. 17(21), pages 1-18, October.
    20. Jyun-You Chen & Shih-Chin Yang & Kai-Hsiang Tu, 2018. "Comparative Evaluation of a Permanent Magnet Machine Saliency-Based Drive with Sine-Wave and Square-Wave Voltage Injection," Energies, MDPI, vol. 11(9), pages 1-15, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2689-:d:787924. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.