Cascade Finite Control Set Model-Free Predictive Control for Permanent Magnet Synchronous Motor
ID:77 View Protection:PUBLIC Updated Time:2023-06-12 18:36:30 Hits:1085 Poster Presentation

Start Time:2023-06-19 09:00(Asia/Shanghai)

Duration:0min

Session:E Poster Session » E1Poster Session 1

Abstract
This paper proposes a cascade finite control set model-free predictive control (MFPC) to improve the dynamic performance and robustness against motor parameters mismatch of the PMSM system. For the speed outer-loop, a model-free predictive speed control method that is easy to implement is designed to improve the dynamic performance and reduce the response time. Meanwhile, the difference in the sampling period for the outer-loop and inner-loop is considered and compensated. Furthermore, a finite control set MFPC strategy is designed for the current inner-loop, which can eliminate the dependence on motor parameters for the predictive current control. Therefore, the robustness against parameters mismatch will be improved. Finally, the simulation is carried out to evaluate the performance of the proposed cascade MFPC by comparing it with the conventional PI and MFPC.
Keywords
cascade;Model-free Predictive Control;PMSM;parameters mismatch
Speaker
Zheng Sun
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Scienci

Yongting Deng
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Jianli Wang
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Haiyang Cao
Changchun Institute of Optics, Fine Mechanics, and Physics, Chinese Academy of Sciences

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Important Date
  • Conference Date

    Jun 16

    2023

    to

    Jun 19

    2023

  • Jun 15 2023

    Contribution Submission Deadline

  • Jul 02 2023

    Registration deadline

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