IMM과 FKF를 이용한 GPS위성 자세제어 시스템 고장 검출

Abstract

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.