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Speed Optimization Control of a Permanent Magnet Synchronous Motor Based on TD3

Author

Listed:
  • Zuolei Hu

    (College of Information Science and Engineering, Hunan University, Changsha 410000, China)

  • Yingjie Zhang

    (College of Information Science and Engineering, Hunan University, Changsha 410000, China)

  • Ming Li

    (School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

  • Yuhua Liao

    (Department of Mechanical, Aerospace and Civil Engineering, the University of Manchester, Manchester M13 9PL, UK)

Abstract

Permanent magnet synchronous motors (PMSMs) are widely used in industrial automation and electric vehicles due to their high efficiency and excellent dynamic performance. However, controlling PMSMs presents challenges such as parameter variations and system nonlinearities. This paper proposes a twin delayed deep deterministic policy gradient (TD3)-based energy-saving optimization control method for PMSM drive systems. The TD3 algorithm uses double networks, target policy smoothing regularization, and delayed actor network updates to improve training stability and accuracy. Simulation experiments under two operating conditions show that the TD3 algorithm outperforms traditional proportional–integral (PI) controllers and linear active disturbance rejection control (LADRC) controllers in terms of reference trajectory tracking, q-axis current regulation, and speed tracking error minimization. The results demonstrate the TD3 algorithm’s effectiveness in enhancing motor efficiency and system robustness, offering a novel approach to PMSM drive system control through deep reinforcement learning.

Suggested Citation

  • Zuolei Hu & Yingjie Zhang & Ming Li & Yuhua Liao, 2025. "Speed Optimization Control of a Permanent Magnet Synchronous Motor Based on TD3," Energies, MDPI, vol. 18(4), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:901-:d:1590292
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    Keywords

    PMSM; TD3; optimization control; energy-saving;
    All these keywords.

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