Artificial neural network speed estimator in a DTC scheme

被引：0

作者：

Cruz, Pedro Ponce ^{[1
]}

Pontecorvo, Flavio Lucio ^{[1
]}

Bada, Jos Ramon Alvarez ^{[1
]}

Monroy, Alfonso ^{[1
]}

Paz, Marco ^{[1
]}

机构：

[1] Inst Tecnol & Estudios Super Monterrey, Campus Ciudad Mexico,Calle Puente 222, Mexico City 14380, DF, Mexico

来源：

PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER SCIENCE AND TECHNOLOGY | 2006年

关键词：

DTC; SVPWM; ANN; sensorless;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Direct torque control (DTC) is known to produce quick and robust response in AC drives. However, during steady state, torque, flux and current ripple occur. An improvement of the electric drive can be obtained using a DTC scheme based on the space vector modulation (SVM) which reduces the torque and flux ripple. The proposed control scheme considers the rotor resistance variation. This paper also discusses the application of artificial neural network (ANN) as a speed estimator. The capability and precision of this scheme as a speed estimator is verified by simulation results, from which it is concluded that the proposed control scheme produces better results than the classical DTC. 505-116 in display pdf

引用

页码：257 / +

页数：2

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