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Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

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  • Meng Shao

    (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yongting Deng

    (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

  • Hongwen Li

    (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

  • Jing Liu

    (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

  • Qiang Fei

    (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.

Suggested Citation

  • Meng Shao & Yongting Deng & Hongwen Li & Jing Liu & Qiang Fei, 2019. "Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM," Energies, MDPI, vol. 12(10), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1857-:d:231483
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    Citations

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    Cited by:

    1. Mengmeng Tian & Hailiang Cai & Wenliang Zhao & Jie Ren, 2023. "Nonlinear Predictive Control of Interior Permanent Magnet Synchronous Machine with Extra Current Constraint," Energies, MDPI, vol. 16(2), pages 1-14, January.
    2. 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.
    3. Fabiano C. Rosa & Edson Bim, 2020. "A Constrained Non-Linear Model Predictive Controller for the Rotor Flux-Oriented Control of an Induction Motor Drive," Energies, MDPI, vol. 13(15), pages 1-18, July.
    4. 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.

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