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

Zuolei Hu, Yingjie Zhang (), Ming Li and Yuhua Liao
Additional contact information
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

Energies, 2025, vol. 18, issue 4, 1-15

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.

Keywords: PMSM; TD3; optimization control; energy-saving (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/4/901/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/4/901/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:4:p:901-:d:1590292

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().