IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i7p1618-d1108512.html
   My bibliography  Save this article

Speed Regulation for PMSM with Super-Twisting Sliding-Mode Controller via Disturbance Observer

Author

Listed:
  • Mingyuan Hu

    (Department of Smart Fab. Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Hyeongki Ahn

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Yoonuh Chung

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Kwanho You

    (Department of Smart Fab. Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
    Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

Abstract

This paper focuses on the speed regulation of a permanent-magnet synchronous motor (PMSM) with an uncertain extended load disturbance. A novel super-twisting sliding-mode control (NSTSMC) was proposed via a nonlinear integral sliding surface and a modified reaching law, effectively suppressing the chattering phenomenon. In addition, the NSTSMC can improve the convergence performance with a 0.04 s settling time, satisfying the super-twisting algorithm stability condition. For the novel integral sliding surface, the integral power term of the system state variables was incorporated into the conventional sliding surface to effectively improve the convergence rate and anti-disturbance ability. Moreover, an extended sliding-mode disturbance observer (ESO) was used to estimate the lumped extended disturbance and add the corresponding feedback compensation value from the sliding-mode disturbance observer to the output of the speed controller for the improved robustness of the system. The ESO-NSTSMC was developed to improve the performance of PMSM speed regulation by combining the advantages of the novel integral sliding surface, achieving a settling time of 0.01 s without overshoot. We confirm the performance of the proposed NSTSMC through a PMSM speed simulation and demonstrate that the controller can enhance the dynamic performance and robustness of the system.

Suggested Citation

  • Mingyuan Hu & Hyeongki Ahn & Yoonuh Chung & Kwanho You, 2023. "Speed Regulation for PMSM with Super-Twisting Sliding-Mode Controller via Disturbance Observer," Mathematics, MDPI, vol. 11(7), pages 1-15, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1618-:d:1108512
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/7/1618/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/7/1618/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hajid Alsubaie & Amin Yousefpour & Ahmed Alotaibi & Naif D. Alotaibi & Hadi Jahanshahi, 2023. "Stabilization of Nonlinear Vibration of a Fractional-Order Arch MEMS Resonator Using a New Disturbance-Observer-Based Finite-Time Sliding Mode Control," Mathematics, MDPI, vol. 11(4), pages 1-14, February.
    2. Fardila Mohd Zaihidee & Saad Mekhilef & Marizan Mubin, 2019. "Robust Speed Control of PMSM Using Sliding Mode Control (SMC)—A Review," Energies, MDPI, vol. 12(9), pages 1-27, May.
    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. Yue Qu & Wenjun Yi, 2023. "An Improved Second-Order Sliding Mode Control for an Interception Guidance System without Angular Velocity Measurement," Mathematics, MDPI, vol. 11(11), pages 1-17, May.

    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. Liqin Wu & Hao Chen & Tingyue Yu & Chengzhi Sun & Lin Wang & Xuerong Ye & Guofu Zhai, 2023. "Robust Design Optimization of the Cogging Torque for a PMSM Based on Manufacturing Uncertainties Analysis and Approximate Modeling," Energies, MDPI, vol. 16(2), pages 1-24, January.
    2. Hassam Muazzam & Mohamad Khairi Ishak & Athar Hanif & Ali Arshad Uppal & AI Bhatti & Nor Ashidi Mat Isa, 2022. "Virtual Sensor Using a Super Twisting Algorithm Based Uniform Robust Exact Differentiator for Electric Vehicles," Energies, MDPI, vol. 15(5), pages 1-18, February.
    3. Zhenjie Gong & Xin Ba & Chengning Zhang & Youguang Guo, 2022. "Robust Sliding Mode Control of the Permanent Magnet Synchronous Motor with an Improved Power Reaching Law," Energies, MDPI, vol. 15(5), pages 1-13, March.
    4. Jiachun Lin & Yuteng Zhao & Pan Zhang & Junjie Wang & Hao Su, 2021. "Research on Compound Sliding Mode Control of a Permanent Magnet Synchronous Motor in Electromechanical Actuators," Energies, MDPI, vol. 14(21), pages 1-17, November.
    5. Majid Roohi & Saeed Mirzajani & Andreas Basse-O’Connor, 2023. "A No-Chatter Single-Input Finite-Time PID Sliding Mode Control Technique for Stabilization of a Class of 4D Chaotic Fractional-Order Laser Systems," Mathematics, MDPI, vol. 11(21), pages 1-22, October.
    6. Kifayat Ullah & Jaroslaw Guzinski & Adeel Feroz Mirza, 2022. "Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation," Energies, MDPI, vol. 15(3), pages 1-13, February.
    7. Feng Jiang & Fan Yang & Songjun Sun & Kai Yang, 2022. "Improved Linear Active Disturbance Rejection Control for IPMSM Drives Considering Load Inertia Mismatch," Energies, MDPI, vol. 15(3), pages 1-22, February.
    8. Abhinandan Routray & Yiza Srikanth Reddy & Sung-ho Hur, 2023. "Predictive Control of a Wind Turbine Based on Neural Network-Based Wind Speed Estimation," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    9. Aleš Hace, 2019. "The Advanced Control Approach based on SMC Design for the High-Fidelity Haptic Power Lever of a Small Hybrid Electric Aircraft," Energies, MDPI, vol. 12(15), pages 1-31, August.
    10. Muhammad Usama & Jaehong Kim, 2021. "Low-Speed Transient and Steady-State Performance Analysis of IPMSM for Nonlinear Speed Regulator with Effective Compensation Scheme," Energies, MDPI, vol. 14(20), pages 1-16, October.
    11. Roland Kasper & Dmytro Golovakha, 2020. "Combined Optimal Torque Feedforward and Modal Current Feedback Control for Low Inductance PM Motors," Energies, MDPI, vol. 13(23), pages 1-16, November.
    12. Irfan Sami & Shafaat Ullah & Zahoor Ali & Nasim Ullah & Jong-Suk Ro, 2020. "A Super Twisting Fractional Order Terminal Sliding Mode Control for DFIG-Based Wind Energy Conversion System," Energies, MDPI, vol. 13(9), pages 1-20, May.
    13. Btissam Majout & Houda El Alami & Hassna Salime & Nada Zine Laabidine & Youness El Mourabit & Saad Motahhir & Manale Bouderbala & Mohammed Karim & Badre Bossoufi, 2022. "A Review on Popular Control Applications in Wind Energy Conversion System Based on Permanent Magnet Generator PMSG," Energies, MDPI, vol. 15(17), pages 1-41, August.
    14. Fawaz W. Alsaade & Mohammed S. Al-zahrani, 2023. "A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators," Mathematics, MDPI, vol. 11(10), pages 1-18, May.
    15. Miguel Angel Hernández-Pérez & Gustavo Delgado-Reyes & Vicente Borja-Jaimes & Jorge Salvador Valdez-Martínez & Marisol Cervantes-Bobadilla, 2023. "An Adaptation of a Sliding Mode Classical Observer to a Fractional-Order Observer for Disturbance Reconstruction of a UAV Model: A Riemann–Liouville Fractional Calculus Approach," Mathematics, MDPI, vol. 11(24), pages 1-23, December.
    16. Farya Golesorkhie & Fuwen Yang & Ljubo Vlacic & Geoff Tansley, 2020. "Field Oriented Control-Based Reduction of the Vibration and Power Consumption of a Blood Pump," Energies, MDPI, vol. 13(15), pages 1-18, July.
    17. Marcin Kamiński & Krzysztof Szabat, 2021. "Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft," Energies, MDPI, vol. 14(12), pages 1-26, June.
    18. Younes Zahraoui & Fardila M. Zaihidee & Mostefa Kermadi & Saad Mekhilef & Ibrahim Alhamrouni & Mehdi Seyedmahmoudian & Alex Stojcevski, 2023. "Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning," Energies, MDPI, vol. 16(11), pages 1-17, May.
    19. Yoon-Seong Lee & Kyoung-Min Choo & Won-Sang Jeong & Chang-Hee Lee & Junsin Yi & Chung-Yuen Won, 2023. "A Virtual Impedance-Based Flying Start Considering Transient Characteristics for Permanent Magnet Synchronous Machine Drive Systems," Energies, MDPI, vol. 16(3), pages 1-17, January.
    20. Mingfei Huang & Yongting Deng & Hongwen Li & Meng Shao & Jing Liu, 2021. "Integrated Uncertainty/Disturbance Suppression Based on Improved Adaptive Sliding Mode Controller for PMSM Drives," Energies, MDPI, vol. 14(20), pages 1-19, October.

    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:jmathe:v:11:y:2023:i:7:p:1618-:d:1108512. 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.