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An Effective Model-Free Predictive Control for LC-Filter Voltage Source Inverters
ID：65 View Protection：PUBLIC Updated Time：2023-06-14 14:48:45 Hits：1079 Poster Presentation

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

Duration：0min

Session：E Poster Session » E1Poster Session 1

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Abstract
The parametric uncertainties have critical effects on output voltage performance of LC-filtered voltage source inverters (VSIs) under model predictive control (MPC). To overcome this known problem, an effective model-free predictive control (MFPC) is proposed. The proposed MFPC realizes robust and accurate voltage predictions by using the capacitor voltage gradients and inverter-side current gradients. Then, the state-space equations of different voltage vectors are established to calculate all the gradients in real time, which can ensure the accuracy of voltage and current gradients. Finally, the practicality of the proposed scheme is demonstrated under ideal and mismatched model. In comparison with conventional MPC, the proposed MFPC not only achieves a comparable voltage performance, but also realizes better robustness.The parametric uncertainties have critical effects on output voltage performance of LC-filtered voltage source inverters (VSIs) under model predictive control (MPC). To overcome this known problem, an effective model-free predictive control (MFPC) is proposed. The proposed MFPC realizes robust and accurate voltage predictions by using the capacitor voltage gradients and inverter-side current gradients. Then, the state-space equations of different voltage vectors are established to calculate all the gradients in real time, which can ensure the accuracy of voltage and current gradients. Finally, the practicality of the proposed scheme is demonstrated under ideal and mismatched model. In comparison with conventional MPC, the proposed MFPC not only achieves a comparable voltage performance, but also realizes better robustness.
Keywords
Speaker
Zheng Yin
Anhui University

Cungang Hu
Anhui University

Tao Rui

Wenping Cao

Zhuangzhuang Feng

Geye Lu
Tsinghua University

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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

Sponsored By
Huazhong University of Science and Technology, China
(IEEE PELS)
IEEE
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