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- W1567172539 abstract "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." @default.
- W1567172539 created "2016-06-24" @default.
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- W1567172539 date "2013-01-01" @default.
- W1567172539 modified "2023-10-18" @default.
- W1567172539 title "An Improved PMSM Drive Architecture Based on BFO and Neural Network" @default.
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- W1567172539 doi "https://doi.org/10.5772/53011" @default.
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