A Satisfactory Vector Selection Model Predictive Control to Reduce Switching Frequency
编号:281 访问权限:仅限参会人 更新:2021-12-03 10:56:49 浏览:524次 口头报告

报告开始:2021年12月17日 10:00(Asia/Shanghai)

报告时间:15min

所在会场:[G] Electric Machine Design and Control [G3] Session 29

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摘要
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.
关键词
model predictive control,reducing switching frequency,satisfactory vector selection
报告人
Qingxuan Wang
Shanghai University

稿件作者
Qingxuan Wang Shanghai University
云鹏 张 Shanghai University
Wenxiang Song Shanghai University
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重要日期
  • 会议日期

    07月11日

    2023

    08月18日

    2023

  • 11月10日 2021

    初稿截稿日期

  • 12月10日 2021

    注册截止日期

  • 12月11日 2021

    报告提交截止日期

主办单位
IEEE IAS
承办单位
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
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