Title :
Permanent magnet synchronous motor modeling and control
Author :
Hung-Yuan Chung ; Shen-liang Lo
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Zhongli, Taiwan
Abstract :
The objective of this study is to achieve permanent magnet synchronous motor (PMSM) speed control in PSIM using a self-tuning PI controller with dual feedforward artificial neural network (DFNN). The two parameters of the PI controller gain, kp and ki, can be controlled online by selftuning in the motor control system verification. The speed response, robustness of anti-load disturbance performance are better compared to a single feedforward artificial neural network (SFNN).
Keywords :
PI control; adaptive control; angular velocity control; feedforward neural nets; machine vector control; neurocontrollers; permanent magnet motors; self-adjusting systems; synchronous motors; DFNN; PI controller gain; PMSM speed control; PSIM; anti load disturbance performance robustness; dual feedforward artificial neural network; field-oriented-control; ki parameter; kp parameter; motor control system verification; permanent magnet synchronous motor modeling; permanent magnet synchronous motor speed control; self- tuning; self-tuning PI controller; speed response; Artificial neural networks; Control systems; Feedforward neural networks; Fuzzy control; Mathematical model; Permanent magnet motors; Torque; Feedforward artificial neural networks; Field-oriented-control; MSM; Selftuning PI controller;
Conference_Titel :
Fuzzy Theory and Its Applications (iFUZZY), 2014 International Conference on
Print_ISBN :
978-1-4799-4590-0
DOI :
10.1109/iFUZZY.2014.7091234
