Application of BEMF-MRAS with Kalman filter in sensorless control of induction motor drive

被引：4

作者：

Brandstetter, Pavel ^{[1
]}

Dobrovsky, Marek ^{[1
]}

Kuchar, Martin ^{[1
]}

Chau Si Thien Dong ^{[2
]}

Hau Huu Vo ^{[2
]}

机构：

[1] Tech Univ Ostrava, VSB, Dept Elect, 17 Listopadu 15-2172, Ostrava 70833, Czech Republic

[2] Ton Duc Thang Univ Ho Chi Minh City, Dept Automat, 19 Nguyen Huu Tho St Tan Phong Ward,Dist 7, Ho Chi Minh City, Vietnam

来源：

ELECTRICAL ENGINEERING | 2017年 / 99卷 / 04期

关键词：

Vector control; Induction motor; Sensorless control; Model reference adaptive system; Speed estimation; DIRECT TORQUE; MACHINE; CONVERTER; ALGORITHM; SYSTEM; PARAMETERS; SIMULATION; MODE;

D O I：

10.1007/s00202-017-0613-4

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：

This paper describes an induction motor speed estimation using the observer with back electromotive force-based model reference adaptive system and Kalman filter. In the first part of the paper, there is a mathematical description of the rotor speed observer. The second part of the paper includes Kalman filter that is used for the filtration of measured stator currents and obtaining their time derivatives. The third part contains a description of the laboratory workplace with the induction motor drive and active load unit that was used for an experimental verification of the rotor speed observer. The last section of the paper shows experimental results that were obtained for different changes in the induction motor speed. The experimental results confirmed expected dynamic properties of the induction motor drive with sensorless control.

引用

页码：1151 / 1160

页数：10

共 32 条

[1] Sensorless Control of Induction-Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation [J].