IMM과 FKF를 이용한 GPS위성 자세제어 시스템 고장 검출 : Fault Detection and Diagnosis in a GPS Satellite Attitude Control System Using Interacting Multiple Model and Federated Kalman Filter

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이준한; 박찬국

Issue Date
GNSS Technology Council
The 17th GNSS Workshop, 11. 4-11.5, 2010, Haevichi Hotel, Jeju
Satellite Attitude Control SystemInteracting Multiple ModelScalar PenaltyFault Detection
This paper presents a new scheme for fault detection and isolation in the satellite system.
The purpose of this paper is to develop detection, isolation and diagnosis algorithms based on the
federated Kalman filter(FKF) and interacting multiple model(IMM) filter for both partial and total faults
in a satellite attitude control system(ACS). In this paper, the federated Kalman filters and a bank of
interacting multiple Kalman filters are utilized for detection and diagnosis of anticipated sensor and
actuator faults in a satellite ACS. Other fault detection, isolation and diagnosis scheme using normal
IMM are compared with proposed FDI scheme. The FDI procedure is developed in two phases. In the
first phase, two local filters and prediction filter are designed to detect sensor faults. In the second
phase, FDI block checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models
are designed to detect wherever actuator faults occur. An important feature of the proposed FDI
scheme can decrease fault isolation time.
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Others_기계항공공학부
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