IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i21p5477-d1512209.html
   My bibliography  Save this article

A Neuroadaptive Position-Sensorless Robust Control for Permanent Magnet Synchronous Motor Drive System with Uncertain Disturbance

Author

Listed:
  • Omar Aguilar-Mejia

    (Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico)

  • Antonio Valderrabano-Gonzalez

    (Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico)

  • Norberto Hernández-Romero

    (Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico)

  • Juan Carlos Seck-Tuoh-Mora

    (Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico)

  • Julio Cesar Hernandez-Ochoa

    (Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico)

  • Hertwin Minor-Popocatl

    (School of Engineering, UPAEP University, 21 Sur 1103, Puebla 72410, Puebla, Mexico)

Abstract

The Permanent Magnet Synchronous Motor (PMSM) drive system is extensively utilized in high-precision positioning applications that demand superior dynamic performance across various operating conditions. Given the non-linear characteristics of the PMSM, a neuroadaptive sensorless controller based on B-spline neural networks is proposed to determine the control signals necessary for achieving the desired performance. The proposed control technique considers the system’s non-linearities and can be adapted to varying operating conditions, all while maintaining a low computational cost suitable for real-time operation. The introduced neuroadaptive controller is evaluated under conditions of uncertainty, and its performance is compared to that of a conventional PI controller optimized using the Whale Optimization Algorithm (WOA). The results demonstrate the viability of the proposed approach.

Suggested Citation

  • Omar Aguilar-Mejia & Antonio Valderrabano-Gonzalez & Norberto Hernández-Romero & Juan Carlos Seck-Tuoh-Mora & Julio Cesar Hernandez-Ochoa & Hertwin Minor-Popocatl, 2024. "A Neuroadaptive Position-Sensorless Robust Control for Permanent Magnet Synchronous Motor Drive System with Uncertain Disturbance," Energies, MDPI, vol. 17(21), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5477-:d:1512209
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/21/5477/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/21/5477/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dongri Shan & Di Wang & Dongmei He & Peng Zhang, 2024. "Position Sensorless Vector Control System for Lawnmower Permanent Magnet Synchronous Motor Based on Extended Kalman Filter," Energies, MDPI, vol. 17(5), pages 1-23, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:21:p:5477-:d:1512209. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.