Open AccessReinforcement learning control method of torque stability of three-phase permanent magnet synchronous motor
Author(s) -
Mengqi Tian,
Ke Wang,
Hongyu Lv,
Wubin Shi
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2183/1/012024
Subject(s) - control theory (sociology) , torque , reinforcement learning , direct torque control , matlab , computer science , controller (irrigation) , pid controller , control engineering , vector control , magnet , reinforcement , stability (learning theory) , engineering , control (management) , induction motor , artificial intelligence , physics , mechanical engineering , thermodynamics , operating system , temperature control , agronomy , structural engineering , voltage , machine learning , biology , electrical engineering
Regarding the control strategy of the permanent magnet synchronous motor, the field-oriented control based on the PI controller have the instability of the output torque. In order to stabilize the output torque of the permanent magnet synchronous motor, this paper adopts reinforcement learning to improve traditional PI controller. Finally, in the MATLAB/Simulink simulation environment, a new control method based on reinforcement learning is established. The simulation results show that the reinforcement learning control method used in this paper can improve the stability of the output torque.