Distributed estimation of time varying bias in relative state measurements

Author(s):  
Mingming Shi
2006 ◽  
Vol 129 (3) ◽  
pp. 352-356 ◽  
Author(s):  
Wen Chen ◽  
Mehrdad Saif

This paper presents a novel fault diagnosis approach in satellite systems for identifying time-varying thruster faults. To overcome the difficulty in identifying time-varying thruster faults by adaptive observers, an iterative learning observer (ILO) is designed to achieve estimation of time-varying faults. The proposed ILO-based fault-identification strategy uses a learning mechanism to perform fault estimation instead of using integrators that are commonly used in classical adaptive observers. The stability of estimation-error dynamics is established and proved. An illustrative example clearly shows that time-varying thruster faults can be accurately identified.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 136687-136701
Author(s):  
Thiruppathirajan S. ◽  
Lakshmi Narayanan R. ◽  
Sreelal S. ◽  
Manoj B. S.

Author(s):  
Bo Yang ◽  
Jian-ping Yuan ◽  
Jian-jun Luo ◽  
Xiao-kui Yue ◽  
Wei-hua Ma

Author(s):  
Motoki UCHIKOSHI ◽  
Nobumichi MIYAHARA ◽  
Keisuke YAGI ◽  
Yoshikazu MORI

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