Torque and Speed Estimator for Induction Motor Using Parallel Neural Networks and Sensor less Technology

被引：1

作者：

Goedtel, A. ^{[1
]}

da Silva, I. N. ^{[2
]}

Serni, P. J. A. ^{[3
]}

Suetake, M. ^{[2
]}

do Nascimento, C. F. ^{[4
]}

da Silva, S. A. O. ^{[1
]}

机构：

[1] Fed Technol Univ Parana, Dept Elect Engn, Cornelio Procopio, PR, Brazil

[2] Univ Sao Paulo, Dept Elect Engn, Sao Carlos, SP, Brazil

[3] State Univ Sao Paulo, Dept Elect Engn, Bauru, SP, Brazil

[4] Fed Univ ABC, Engn Ctr, Santo Andre, SP, Brazil

来源：

IECON: 2009 35TH ANNUAL CONFERENCE OF IEEE INDUSTRIAL ELECTRONICS, VOLS 1-6 | 2009年

基金：

巴西圣保罗研究基金会;

关键词：

D O I：

10.1109/IECON.2009.5414705

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Many electronic drivers for induction motor control are based on sensorless technologies. The proposal of this work is to present an efficient torque and speed estimator for induction motor steady state operations by using artificial neural networks. The proposed method is based on off-line training which considers different types of loads and a wide range of supply voltage. The inputs of the network are the induction motor RMS voltage and current. Resides, the estimation processing effort is reduced to a simple matrix solving after the neural network is trained. Simulation and experimental results are also presented to validate the proposed approach.

引用

页码：1267 / +

页数：2

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