Robust fault diagnosis for satellite attitude systems using neural state space models
Document Type
Conference Proceeding
Publication Date
11-30-2005
Publication Title
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume
2
First Page
1955
Keywords
Aerospace applications, Fault diagnosis, Neural networks
Last Page
1960
Abstract
In this paper, a robust fault detection and diagnosis scheme using neural state space models has been developed for a class of nonlinear systems. The neural state space models are adopted to estimate the modeling uncertainties in the states and outputs of the system. Subsequently, a residual is generated to identify the characteristics of the fault. Moreover, the robustness, sensitivity and stability properties of the proposed fault detection and diagnosis scheme are rigorously derived. Finally, the neural state space model based fault detection and diagnosis scheme is applied to a satellite attitude control system and the simulation results demonstrated its good performance. © 2005 IEEE.
ISSN
1062922X
Recommended Citation
Wu, Qing and Saif, Mehrdad. (2005). Robust fault diagnosis for satellite attitude systems using neural state space models. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2, 1955-1960.
https://scholar.uwindsor.ca/electricalengpub/399