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

Abstract

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.