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Cascade Filter Structure for Sensor-Actuator Fault Detection and Isolation of Satellite Attitude Control System

Cited 5 time in Web of Science Cited 8 time in Scopus
Authors
Lee, Junhan; Park, Chan Gook
Issue Date
2012-06
Publisher
Springer
Citation
International Journal of Control, Automation, and Systems (2012) 10(3):506-516
Keywords
DKFfault identificationFDIIMMKalman filterpartial faultsatellitetotal fault
Abstract
This paper presents a new scheme for fault detection and isolation in a satellite system. The
purpose of this paper is to develop detection, isolation and identification algorithms based on a cascade
filter for both total and partial faults in a satellite attitude control system (ACS). The cascade filter consists
of a decentralized Kalman filter (DKF) and a bank of interacting multiple model (IMM) filters.
The cascade filter is utilized for detection and diagnosis of anticipated sensor and actuator faults in a
satellite ACS. Other fault detection and isolation (FDI) schemes are compared with the proposed FDI
scheme. The FDI procedure using a cascade filter was developed in three stages. In the first stage, two
local filters and a master filter detect sensor faults. In the second stage, the FDI scheme checks sensor
residuals to isolate sensor faults, and 11 Extended Kalman filters with actuator fault models detect
wherever actuator faults occur. In the third stage of the FDI scheme, four filters identify the fault type,
which is either a total or partial fault. An important feature of the proposed FDI scheme is that it can
decrease fault isolation time and accomplish not only fault detection and isolation but also fault type
identification using a scalar penalty in the conditional density function.
ISSN
1598-6446
Language
English
URI
https://hdl.handle.net/10371/77208
DOI
https://doi.org/10.1007/s12555-012-0307-7
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Journal Papers (저널논문_기계항공공학부)
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