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TECHNICAL BRIEFS

Observer-Based Fault Diagnosis of Satellite Systems Subject to Time-Varying Thruster Faults

[+] Author and Article Information
Wen Chen

School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada

Mehrdad Saif1

School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canadasaif@ensc.sfu.ca

1

Author to whom correspondence should be addressed.

J. Dyn. Sys., Meas., Control 129(3), 352-356 (Aug 09, 2006) (5 pages) doi:10.1115/1.2719773 History: Received September 21, 2005; Revised August 09, 2006

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.

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Copyright © 2007 by American Society of Mechanical Engineers
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Figures

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Figure 1

Fault estimation by the ILO: A constant fault

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Figure 2

Fault estimation by the ILO: A periodic fault.

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Figure 3

Fault estimation by the ILO: An arbitrary time-varying fault.

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Figure 4

Fault estimation by an adaptive observer: A time-varying fault

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Figure 5

Fault estimation: A combined time-varying fault

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