An Improved PMSM Drive Architecture Based on BFO and Neural Network

[摘要] In this paper, an improved robust vector control strategy is designed to drive the Permanent magnet synchronous motor in a wide speed range mode. The designed control method guarantees the precision and robustness of speed regulation performance by using recurrent neural network architecture. The stator current controller parameter tuning problems, which characterize this control strategy, are resolved using a bacterial foraging optimization algorithm to find the optimal parameters of the current controllers used. A field weakening control algorithm generates an adaptive magnetizing current command to achieve the desired high speed mode. The robustness and effectiveness of the global control scheme are verified through computer simulations established under a Matlab-Simulink environment.

[学科分类] 自动化工程

[关键词] Motor Speed Drive;PMSM;Vector Control;High Speed;BFO Algorithm;Recurrent Neural Network