Data-Driven Predictive Control with Inherent Update Method for Two-Level Voltage Source Inverters
编号:143 访问权限:公开 更新:2023-06-13 20:32:46 浏览:387次 口头报告

报告开始:2023年06月18日 09:30(Asia/Shanghai)

报告时间:20min

所在会场:[S] Oral Session [S2] Oral Session 2 & Oral Session 5

摘要
This paper proposes an inherent and effective method for updating the database which is critical for the model-free predictive controller. In contrast to existing update methods which require complex analytical expressions, a unified analytical update model is proposed as a sum of the actual current and input control gradients.  The effectiveness of the proposed controller is validated in a two-level voltage source inverter connected to the grid and an RLE load. The simulation results show that DDPC effectively cancels the stagnant mode and compared with MPC, DDPC provides better current performance at normal conditions and has higher robustness under parameter mismatches. 
关键词
MODEL PREDICTIVE CONTROL;Model-free Predictive Control;voltage source converter
报告人
Paul Gistain Ipoum Ngome
null

Mon-Nzongo Daniel

Tao Jin
Fuzhou University

Jinquan Tang

Jose Rodriguez
Universidad San Sebastian

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重要日期
  • 会议日期

    06月16日

    2023

    06月19日

    2023

  • 06月15日 2023

    报告提交截止日期

  • 07月02日 2023

    注册截止日期

主办单位
Huazhong University of Science and Technology, China
(IEEE PELS)
IEEE
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