An Improved Triple-Vector Modulated Model Predictive Control Method for Permanent Magnet Synchronous Motor
ID:92 View Protection:PUBLIC Updated Time:2023-06-13 18:37:03 Hits:1124 Poster Presentation

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

Duration:0min

Session:E Poster Session » E2Poster Session 2

Abstract
Model predictive control (MPC) has been widely used in motor control, and modulated model predictive control (MMPC) has been derived. However, in the conventional MMPC, the action time of the basic voltage vector is calculated by the inverse ratio of the cost function, which lacks a strictly theoretical basis. To enhance the theoretical basis of the MMPC, an improved triple-vector MMPC is proposed. First, two adjacent dual-vectors are synthesized by the conventional method. Then, the Helen's formula and geometric relationship between the two dual-vectors are used to scale and synthesize the triple-vectors. Finally, the simulation verifies the effectiveness of the proposed method.
Keywords
modulated model predictive control;cost function;triple-vector;theoretical basis;Helen
Speaker
Leilei Guo
Associate professor College of Electrical and Information Engineering, Zhengzhou University of Light Industry

Pu Zhong

Han Xiao
Zhengzhou University of Light Industry

Xu Wei

Liu Dong

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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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Huazhong University of Science and Technology, China
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