IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2649-d1405175.html
   My bibliography  Save this article

Improved Model-Free Deadbeat Predictive Current Controller for PMSMs Based on Ultralocal Model and H ∞ Norm

Author

Listed:
  • Yiming Fang

    (School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China)

  • Junlei Chen

    (School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China)

Abstract

This article proposes an improved model-free deadbeat predictive current control (MFCC) method for permanent magnet synchronous motors (PMSMs) based on the ultralocal model and H ∞ norm. Firstly, the traditional deadbeat predictive current control (DPCC) method is introduced and a theoretical analysis is conducted on its sensitivity to parameters. Building upon this, the limitations of model dependence and the limited robustness of the deadbeat predictive current control method based on the extended state observer (ESO-DPCC) are theoretically analyzed. Furthermore, an improved MFCC method based on the ultralocal model is proposed, and the influence of the observer on MFCC is theoretically analyzed. This study combined the proposed method with the H ∞ norm, and the optimal coefficients of the observer were tuned to enhance the robustness and dynamic performance of the current loop. Finally, the proposed algorithms were validated on a 400 W PMSM platform.

Suggested Citation

  • Yiming Fang & Junlei Chen, 2024. "Improved Model-Free Deadbeat Predictive Current Controller for PMSMs Based on Ultralocal Model and H ∞ Norm," Energies, MDPI, vol. 17(11), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2649-:d:1405175
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2649/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/11/2649/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2649-:d:1405175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.