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Volume 9 Issue 12
Dec.  2022

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2022  >  9(12): 2087-2105
T. Li, X. D. Sun, G. Lei, Z. B. Yang, Y. G. Guo, and J. G. Zhu, “Finite-control-set model predictive control of permanent magnet synchronous motor drive systems — An overview,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2087–2105, Dec. 2022. doi: 10.1109/JAS.2022.105851
Citation: T. Li, X. D. Sun, G. Lei, Z. B. Yang, Y. G. Guo, and J. G. Zhu, “Finite-control-set model predictive control of permanent magnet synchronous motor drive systems — An overview,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2087–2105, Dec. 2022. doi: 10.1109/JAS.2022.105851
shu

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems — An Overview

doi: 10.1109/JAS.2022.105851
  • 1.

    Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China

  • 2.

    School of Electrical and Data Engineering, University of Technology Sydney, Sydney NSW 2007, Australia

  • 3.

    School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China

  • 4.

    School of Electrical and Information Engineering, University of Sydney, Sydney NSW 2006, Australia

Funds:  This work was supported in part by the National Natural Science Foundation of China (51875261), the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX21_3331), and the Faculty of Agricultural Equipment of Jiangsu University (NZXB20210103)
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    Abstract
  • Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

     

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