• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1180-1188
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

• 한국항공우주학회지
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• 제33권3호
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• pp.57-64
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• 2005

2자유도 관성센서는 두 입력축이 기계적으로 연관되어 있기 때문에 해당하는 관성센서의 두 입력축에 동시에 고장이 발생할 확률이 매우 높다. 따라서 하드웨어 여분만으로 고장검출 및 분리를 수행하기 위해서는 최소한 4개의 관성센서를 사용하여야 한다. 2자유도 관성센서를 3개 중첩해서 사용하는 경우 기존의 하드웨어 여분기법으로는 고장검출은 가능하나 고장분리가 불가능하다. 본 논문에서는 이러한 문제점을 개선하기 위해서 비선형 필터인 Unscented Kalman Filter를 이용하여 얻은 정보를 해석적 여분으로 활용하여, 하드웨어 여분과 해석적 여분을 동시에 고려한 복합 고장검출기법을 제안하였다. 제안한 복합 고장검출기법의 성능을 검증하기 위해서 비선형 항공기 수치 시뮬레이션을 수행하였다.

• International Journal of Aeronautical and Space Sciences
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• 제7권1호
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• pp.73-83
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• 2006

In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.