Observer-based fault diagnosis of satellite systems subject to time-varying thruster faults
Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Fault identification, Iterative learning observer, Satellite systems, Time-varying thruster faults
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. Copyright © 2007 by ASME.
Chen, Wen and Saif, Mehrdad. (2007). Observer-based fault diagnosis of satellite systems subject to time-varying thruster faults. Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, 129 (3), 352-356.