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Predictive Current Control of Sensorless Linear Permanent Magnet Synchronous Motor

Author

Listed:
  • He Wang

    (School of Automation, China University of Geosciences, Wuhan 430074, China)

  • Tao Wu

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China
    Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China)

  • Youguang Guo

    (Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia)

  • Gang Lei

    (Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia)

  • Xinmei Wang

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China
    Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China)

Abstract

In the vector control system of a tubular oscillating permanent magnet synchronous linear motor, it is difficult to obtain accurate feedback information from the conventional mechanical sensors under bad and complex working conditions. This paper presents a new predictive current control designed to estimate the speed of the tubular oscillation permanent magnet synchronous linear motor. It implements two control techniques: The first technique is using the sliding-mode observer’s speed observer for speed estimation. The second is to design a deadbeat predictive current control to replace the PI regulator in the conventional current loop; it solves the difficulties of global optimization and PI parameter setting. The simulation and experimental results show that this method gives a good dynamic performance.

Suggested Citation

  • He Wang & Tao Wu & Youguang Guo & Gang Lei & Xinmei Wang, 2023. "Predictive Current Control of Sensorless Linear Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 16(2), pages 1-14, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:628-:d:1025469
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    References listed on IDEAS

    as
    1. Mohammad Alathamneh & Haneen Ghanayem & Xingyu Yang & R. M. Nelms, 2022. "Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Proportional-Resonant Control Method," Energies, MDPI, vol. 15(19), pages 1-17, September.
    2. Tian-Hua Liu & Kai-Hsiang Chang & Jia-Han Li, 2021. "Design and Implementation of Periodic Control for a Matrix Converter-Based Interior Permanent Magnet Synchronous Motor Drive System," Energies, MDPI, vol. 14(23), pages 1-29, December.
    3. Baochao Wang & Yangrui Wang & Liguo Feng & Shanlin Jiang & Qian Wang & Jianhui Hu, 2019. "Permanent-Magnet Synchronous Motor Sensorless Control Using Proportional-Integral Linear Observer with Virtual Variables: A Comparative Study with a Sliding Mode Observer," Energies, MDPI, vol. 12(5), pages 1-12, March.
    4. Xin Gu & Yiyang Li & Wei Chen & Xuefeng Jin, 2022. "Improved Deadbeat Predictive Control Based Current Harmonic Suppression Strategy for IPMSM," Energies, MDPI, vol. 15(11), pages 1-19, May.
    5. Jiachun Lin & Yuteng Zhao & Pan Zhang & Junjie Wang & Hao Su, 2021. "Research on Compound Sliding Mode Control of a Permanent Magnet Synchronous Motor in Electromechanical Actuators," Energies, MDPI, vol. 14(21), pages 1-17, November.
    6. Xiaoli Zeng & Weiqing Wang & Haiyun Wang, 2022. "Adaptive PI and RBFNN PID Current Decoupling Controller for Permanent Magnet Synchronous Motor Drives: Hardware-Validated Results," Energies, MDPI, vol. 15(17), pages 1-16, August.
    7. Seung-Taik Kim & In-Sik Yoon & Sung-Chul Jung & Jong-Sun Ko, 2022. "Robust Sensorless Control of Interior Permanent Magnet Synchronous Motor Using Deadbeat Extended Electromotive Force Observer," Energies, MDPI, vol. 15(20), pages 1-16, October.
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    Citations

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    Cited by:

    1. Laiwu Luo & Feng Yu & Lei Ren & Cheng Lu, 2023. "Parameter-Free Model Predictive Current Control for PMSM Based on Current Variation Estimation without Position Sensor," Energies, MDPI, vol. 16(19), pages 1-14, September.
    2. Youguang Guo & Yunfei Yu & Haiyan Lu & Gang Lei & Jianguo Zhu, 2024. "Enhancing Performance of Permanent Magnet Motor Drives through Equivalent Circuit Models Considering Core Loss," Energies, MDPI, vol. 17(8), pages 1-17, April.

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