Neural computation based vector controlled asynchronous motor fed by three levels NPC

被引：3

作者：

Douiri M.R. ^{[1
]}

Hbib M. ^{[2
]}

Cherkaoui M. ^{[2
]}

机构：

[1] Superior School of Technology - Essaouira, Cadi Ayyad University, B.P. 383 Essaouira El Jadida, Essaouira

[2] Department of Electrical Engineering, Mohammadia Engineering School, Mohammed V University, Ibn-Sina Avenue, Agdal-Rabat

来源：

Energy Systems | 2017年 / 8卷 / 04期

关键词：

Artificial neural network; Direct torque control; Induction motor; Three levels inverter;

D O I：

10.1007/s12667-016-0207-7

中图分类号：

学科分类号：

摘要：

This study presents an improved direct torque control based on artificial neural network techniques fed by a three levels neutral-point-clamped inverter for high power asynchronous motor drive. Indeed, the ANN is divided into four sub-networks, which are individually trained: flux estimation (supervised) with dynamic neurons, torque calculation (fixed-weight) with square neurons, flux angle encoder and magnitude calculation (supervised and fixed-weight) with “logsig” neurons and “tansig” neurons. The back-propagation learning rule is used to design the supervised neural network. The simple structure network facilitates a short training and processing times. The validity of the proposed approaches is confirmed by the simulation. © 2016, Springer-Verlag Berlin Heidelberg.

引用

页码：693 / 707

页数：14

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