• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.85-85
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• 2000

In this paper, we propose a novel robust fault isolation filter design method using the left eigenstructure assignment scheme proposed b\ulcorner author. An eigenstructure assignment methodology that satisfies the required fault isolation conditions is also proposed. The proposed method guarantees that the corrupted ${\gamma}$ simultaneous faults can be isolated when the numbers of available output measurements are ${\gamma}$.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.384-392
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• 2001

In this paper, we propose a novel robust fault isolation filter design method using the left eigenstructure assignment scheme proposed by the authors. The proposed method guarantees that the ${\gamma}$ simultaneous faults can be isolated when the number of available outpur measurements is ${\gamma}$. Moreover, if there exist redundant output measurements, the eigenvaluses of te filter system can be assigned to the desired position or the filter can be designed robustly to, the system parameter variation. Liu & Si developed a filter design method which has the same purpose, fault isolation. However their method cannot use the redundant freedom of the output matrix C. The proposed filter can use the redundant freedom of the matrix C effectively. Beside this in this paper, an eigenstructure assignment methodology that satisfies the required fault isolation conditions is also proposed. The proposed fault isolation filter was applied for isolating the simultaneous faults to a VTOL aircraft in order to verify the fault isolation performance.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.270-276
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• 2002

An integrated robust fault diagnosis and fault accommodation strategy for a class of linear stochastic systems subjected to unknown disturbances is presented under the assumption that only a single fault may occur at a given time. The strategy is based on the fault isolation and estimation using a bank of robust two-stage Kalman filters and introduction of the additive compensation input for cancelling out the fault's effect on the system. Each filter is set up such that the residual is decoupled from unknown disturbances and fault with the influence vector designed in the filter. Simulation results for the simplified longitudinal flight control system with parameter uncertainties, process and sensor noises demonstrate the effectiveness of the present approach.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.80-86
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• 2010

We propose a spacecraft attitude estimation algorithm using a federated unscented Kalman filter. For nonlinear spacecraft systems, the unscented Kalman filter provides better performance than the extended Kalman filter. Also, the decentralized scheme in the federated configuration makes a robust system because a sensor fault can be easily detected and isolated by the fault detection and isolation algorithm through a sensitivity factor. Using the proposed algorithm, the spacecraft can continuously perform a given mission despite navigation sensor faults. Numerical simulation is performed to verify the performance of the proposed attitude estimation algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.107-116
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• 2003

This paper presents a systematic design methodology for fault tolerant controller against a fault in actuators and sensors of linear stochastic systems with uncertainties. The scheme is based on fault detection and diagnosis(isolation and estimation) using a bank of robust two-stage Kalman filters, and accommodation of the actuator fault by eigenstructure assignment and immediate compensation of the sensor's faulty measurement. In order to clarify the fault feature in test statistics of residual, noise reduction method is given by multi-scale discrete wavelet transform. The effectiveness of our approach Is shown via simulations for a VTOL(vertical take-off and landing) aircraft subjected to parameter variations, external disturbances, process and sensor noises.