Since any disturbances and faults may lead to significant performance degradation in practical dynamical systems, it is essential for a system to be robust to disturbances and, at the same time, sensitive to faults. For this purpose, the authors propose an optimal robust fault-detection filter for linear discrete time-varying systems. The algorithm solves linear matrix inequalities to obtain the optimal robust H∞ estimator, minimises the H∞ norm from uncertain disturbances to estimation errors and uses H− index to maximise the minimum effect of faults on the residual output of the filter. This approach is applied to the micro-electro-mechanical system-based inertial navigation system/global positioning system; and the simulation results show that the new algorithm can achieve small estimation errors and has high sensitivity to faults.
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Shi et al. (2012) studied this question.
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