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Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.
Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems, it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose, this paper proposes a robust fault-detection filter for linear discrete time- varying systems. The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors, and H_index to maximize the minimum effect of faults on the residual output of the filter. This approach is applied to the MEMS-based INS / GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.