A Satisfactory Vector Selection Model Predictive Control to Reduce Switching Frequency
ID:281 View Protection:ATTENDEE Updated Time:2021-12-03 10:56:49 Hits:1116 Oral Presentation

Start Time:2021-12-17 10:00(Asia/Shanghai)

Duration:15min

Session:G Electric Machine Design and Control » G3Session 29

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Abstract
The traditional model predictive direct current control selects the best switching state based on the principle of the smallest cost function, without considering the restriction on the switching frequency. This paper proposes a model predictive control method with satisfactory vector selection to reduce the switching frequency. This method selects several alternative voltage vectors in each sampling period based on the principle of minimum current error, and the historical switching state is considered meanwhile. Further, a satisfactory voltage vector is selected among these voltage vectors by constraints of reducing switching times. The simulation results indicate that the proposed method effectively reduces the switching frequency and maintains the system performance.
Keywords
model predictive control,reducing switching frequency,satisfactory vector selection
Speaker
Qingxuan Wang
Shanghai University

Submission Author
Qingxuan Wang Shanghai University
云鹏 张 Shanghai University
Wenxiang Song Shanghai University
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Important Date
  • Conference Date

    Jul 11

    2023

    to

    Aug 18

    2023

  • Nov 10 2021

    Draft paper submission deadline

  • Dec 10 2021

    Registration deadline

  • Dec 11 2021

    Contribution Submission Deadline

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Organized By
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST