Source Code for Permanent Magnet Synchronous Motor Fault Diagnosis and Fault-Tolerant Control Using Kalman Filter Technology

In this paper, the authors provide a comprehensive introduction to the source code for permanent magnet synchronous motor fault diagnosis and fault-tolerant control based on Kalman filter technology. The research was published and indexed in the ICACMVE'07 conference proceedings. The authors conduct an in-depth exploration of both Kalman filter principles and the operational characteristics of permanent magnet synchronous motors, proposing an effective method for fault diagnosis and fault-tolerant control. The implementation employs recursive state estimation algorithms for real-time system monitoring and incorporates residual analysis for fault detection. Furthermore, the paper details the source code implementation process and results, including key functions for sensor data processing, state prediction, and control signal adjustment. The practicality and feasibility of the method are thoroughly evaluated and analyzed through experimental validation. Overall, this research provides novel approaches and methodologies for fault diagnosis and fault-tolerant control in permanent magnet synchronous motors, representing significant contributions to related research fields.