Fault-Tolerant Control of Speed Sensor for PMSM Based on Improved Maximum-Likelihood Voting

被引：0

作者：

Dan, Ning ^{[1
]}

Yuan, Yuhao ^{[1
]}

Feng, Jin ^{[1
]}

机构：

[1] Nanjing Tech Univ, Coll Elect Engn & Control Sci, Nanjing, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2019 IEEE 8TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

permanent magnet synchronous motor; extended Kalman filter; data fusion; maximum-likelihood voting; fault-tolerant control; OBSERVER; DRIVES;

D O I：

10.1109/itaic.2019.8785874

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to improve the reliability of vector control system of permanent magnet synchronous motor (PMSM), a fault-tolerant control (FTC) strategy of speed sensor based on improved maximum-likelihood voting (MLV) algorithm is proposed. Extended Kalman filter (EKF) is designed to estimate motor speed and serves as the basis for MLV preparation. The MLV is improved by using data fusion technology to process speed information. When the speed sensor fails, fault isolation and reconfiguration of the system structure can be accomplished naturally. The simulation results show that the proposed FTC strategy can maintain the high performance and uninterrupted operation of PMSM even when the speed sensor fails.

引用

页码：1511 / 1515

页数：5

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