多層ニューラルネットワークを用いたPMSMの低速域センサレス制御の高性能化

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2021/10/01

タイトル(英語): Improvement of Low-speed Sensorless Control with Multi-Layer Neural Network

著者名: 前川　佐理（成蹊大学理工学部システムデザイン学科），田中　亜実（成蹊大学理工学部システムデザイン学科）

著者名(英語): Sari Maekawa (Department of Systems Design Engineering, Faculty of Science and Technology, Seikei University), Ami Tanaka (Department of Systems Design Engineering, Faculty of Science and Technology, Seikei University)

キーワード: センサレス，PMSM，低速，突極性，ニューラルネットワーク，電流微分 sensorless，PMSM，slow，saliency，Neural Network，current slope

要約(英語): In recent years, there has been an increasing demand for position sensorless control in PMSM drives, and various methods have been studied. Switching noise is a problem in the low-speed sensorless control method that uses the current slope during PWM. Furthermore, another problem is that the inductance does not appear in a sinusoidal distribution owing to magnetic saturation.In this paper, we improve the sensorless control method that estimates the position from the current slope during PWM, which is greatly affected by switching. Additionally, we build a multi-layer neural network (NN) that directly estimates the position signals by learning a large amount of current data, and verify the driving results in the low-speed range when the learned NN is incorporated into real-time control.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.141 No.10 （2021）

本誌掲載ページ: 749-762 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/141/10/141_749/_article/-char/ja/