A New Approach to Fault Diagnosis for Satellite Control Systems Based on Machine Learning
Based on the traditional method of analytical redundancy fault diagnosis, the advanced machine learning technology is combined with the model-based fault diagnosis so as to form a new intelligent approach to the fault diagnosis for satellite control systems. The support vector regression technique in statistical learning theory is employed to model the control system with a little sampling data firstly. Then the feasibility of detecting and identifying faults for the satellite attitude control system with the Mahalanobis distance is analyzed in detail. Finally a set of fault-detection observers are designed and implemented based on the residual evaluation. The simulation result indicates that the diagnosing method proposed in this paper is characterized with light computation burden and good real-time performance.
Satellite Attitude Control System Fault Diagnosis SVM
Fei Yan Mingjian Li
School of Technology, Beijing Forestry University, Beijing, China
国际会议
沈阳
英文
1070-1076
2011-11-22（万方平台首次上网日期，不代表论文的发表时间）