ニューラルネットワークを用いた誘導電動機のベクトル制御

概要

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Slip frequency vector control is generally used for variable speed induction motor drives, due to its excellent response characteristics. It is however sensitive to the variation of motor parameters since the flux current and slip frequency commnands are computed using the motor parameters. As a result, the system performance will be degraded if the controller parameters do not match the motor parameters.The authors propose a new approach of vector control in which quick responses and system robustness are concurrently obtained by the learning capabilities of neural network. In the newly developed method, controller parameters are learned in real-time at medium and high speeds. Using these learned parameters, the low speed performance of the controller can also be greatly improved.This paper describes the theoretical analysis, simulation and experimental results of the proposed method.
社団法人電気学会の論文