Reinforcement learning based non-linear feedback synchronous control technology for permanent magnet synchronous motors

Jia Li

doi:10.1117/12.3011006

1 December 2023 Reinforcement learning based non-linear feedback synchronous control technology for permanent magnet synchronous motors

Jia Li

Author Affiliations +

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 1294006 (2023) https://doi.org/10.1117/12.3011006
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

Current synchronous control techniques for non-linear feedback in permanent magnet synchronous motors have large synchronous control time delays due to weak sensor signals. For this reason, a reinforcement learning based synchronous control technique for non-linear feedback of permanent magnet synchronous motors is proposed. A full speed position sensor is set up. Design of a master control centre based on reinforcement learning and reinforced processing of sensor signals. Design of non-linear feedback controller. Implementing synchronous control of permanent magnet synchronous motors based on feedback information. Simulation experiments have shown that this technology has a short response time and can significantly reduce the synchronization control delay of permanent magnet synchronous motors, with an average delay of 0.56 seconds. It has high practical application value.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jia Li "Reinforcement learning based non-linear feedback synchronous control technology for permanent magnet synchronous motors", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 1294006 (1 December 2023); https://doi.org/10.1117/12.3011006

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