Repetitive learning observer based actuator fault detection, isolation, and estimation with application to a satellite attitude control system

Document Type

Conference Proceeding

Publication Date

12-1-2007

Publication Title

Proceedings of the American Control Conference

First Page

414

Last Page

419

Abstract

An actuator fault isolation and estimation (FIE) scheme using a bank of repetitive learning observers (RLOs) for a class of discrete-time nonlinear systems is investigated in this paper. The parameters of these observers are repetitively up-dated using a Proportional-Derivative type learning algorithm at each sampling time. Based on the proposed RLOs, a group of diagnostic residuals are generated correspondingly. An actuator fault is located when only one residual goes to zero while the others do not. The parameter of the observer that locates the fault specifies the fault. Theoretically, sufficient conditions for the proposed fault detection, isolation and estimation scheme are derived. Practically, the proposed FIE scheme is applied to a satellite attitude control system, and the simulation results demonstrate its effectiveness. © 2007 IEEE.

DOI

10.1109/ACC.2007.4282182

ISSN

07431619

ISBN

1424409888,9781424409884

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