IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1736931.html
   My bibliography  Save this article

Current Control of Permanent Magnet Synchronous Motors Using Improved Model Predictive Control

Author

Listed:
  • Muhammad Kashif Nawaz
  • Manfeng Dou
  • Saleem Riaz
  • Muhammad Usman Sardar
  • Amin Jajarmi

Abstract

Model predictive control (MPC) is a powerful tool for the control of permanent magnet synchronous motors. However, conventional MPC permits using a single voltage vector during one control interval. This results in higher current distortions and large torque ripples. Sensitivity to control parameters is another issue associated with conventional MPC. The duty cycle suggests using an active vector and a null vector during one sampling interval. The method needs excessive computational and prediction effort. Furthermore, a necessary zero vector as the second vector might not give the optimal results. To overcome the problems of computational burden, this paper proposes that a reference voltage vector can be calculated and used to determine the voltage vector to be used for the next interval. This reduces the computational effort to a minimum. Furthermore, it is proposed that the second vector can either be active or null. To overcome the problem of parameter dependence, an electromotive force is calculated on basis of previous values. Simulations have been carried out to verify the efficacy of the proposed method.

Suggested Citation

  • Muhammad Kashif Nawaz & Manfeng Dou & Saleem Riaz & Muhammad Usman Sardar & Amin Jajarmi, 2022. "Current Control of Permanent Magnet Synchronous Motors Using Improved Model Predictive Control," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, June.
  • Handle: RePEc:hin:jnlmpe:1736931
    DOI: 10.1155/2022/1736931
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/1736931.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/1736931.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/1736931?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Siddique Akbar & Toomas Vaimann & Bilal Asad & Ants Kallaste & Muhammad Usman Sardar & Karolina Kudelina, 2023. "State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions," Energies, MDPI, vol. 16(17), pages 1-44, September.
    2. Mengmeng Tian & Hailiang Cai & Wenliang Zhao & Jie Ren, 2023. "Nonlinear Predictive Control of Interior Permanent Magnet Synchronous Machine with Extra Current Constraint," Energies, MDPI, vol. 16(2), pages 1-14, January.

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:1736931. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.