Fault Prognosis Approach for Satellite Attitude Control System Based on T-S Model and Time Series Analysis

Abstract A new method based on T-S fuzzy model and time series analysis is proposed for predicting faults in satellite attitude control system. Firstly, satellite attitude control system with nonlinearity and uncertainty is modeled. The residual errors can be obtained by fuzzy parity equation and they are only sensitive to the output of specific actuators (or sensors). Secondly, the time series of the output errors are used to build the autoregressive (AR) model. Therefore, the faults in the satellite attitude control system are predicted by using the AR model. Finally, the results of fault prognosis are given by fault probability. The confidence factor is determined which shows the confidence level of the fault prognosis.

[1]  Jie Zhao,et al.  Equipment Fault Forecasting Based on ARMA Model , 2007, 2007 International Conference on Mechatronics and Automation.

[2]  Huang Hai-yu.  A Survey of Spacecraft Autonomous Fault Diagnosis Research , 2009 .

[3]  Song Hua,et al.  An approach to sensor fault diagnosis based on fully-decoupled parity equation and parameter estimation , 2002, Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527).

[4]  G. Lindgren,et al.  Optimal prediction of catastrophes in autoregressive moving-average processes , 1996 .

[5]  Zhang Hongyue,et al.  Fuzzy basis function network based approach for fault information detection in unknown systems , 2003 .

[6]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Min Xie,et al.  The use of ARIMA models for reliability forecasting and analysis , 1998 .

[8]  Liang Ge,et al.  Fatigue life prediction of rear axle using time series model , 2008, 2008 International Conference on Control, Automation and Systems.