An overview of robust model-based fault diagnosis for satellite systems using sliding mode and learning approaches
Document Type
Conference Proceeding
Publication Date
12-1-2007
Publication Title
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
First Page
3159
Last Page
3164
Abstract
In this paper, our recent work on robust fault diagnosis (FD) for satellite control systems using sliding mode and learning approaches are summarized. Firstly, a variety of nonlinear mathematical models for satellites are described and analyzed for the purpose of fault diagnosis. Then, fault diagnostic sliding mode observer with time-varying gains is presented and analyzed. Two classes of learning estimators are integrated with the sliding mode observer to construct robust fault diagnosis schemes, which are investigated as well. Finally, conclusions and future work on the health monitoring and fault diagnosis for satellite systems are proposed. © 2007 IEEE.
DOI
10.1109/ICSMC.2007.4414209
ISSN
1062922X
ISBN
1424409918,9781424409914
Recommended Citation
Wu, Qing and Saif, Mehrdad. (2007). An overview of robust model-based fault diagnosis for satellite systems using sliding mode and learning approaches. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 3159-3164.
https://scholar.uwindsor.ca/electricalengpub/377