Optimal robust fault-detection filter for micro-electro-mechanical system-based inertial navigation system/global positioning system

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Optimal robust fault-detection filter for micro-electro-mechanical system-based inertial navigation system/global positioning system

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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.

Inspec keywords: H∞ filters; inertial navigation; fault diagnosis; microsensors; time-varying systems; linear systems; discrete time systems; linear matrix inequalities; uncertain systems; H∞ optimisation; Global Positioning System; estimation theory

Other keywords: dynamical system; microelectromechanical system-based inertial navigation system; optimal robust fault-detection filter; uncertain disturbance; optimal robust H estimator; global positioning system; linear discrete time-varying system; H- index; linear matrix inequalities; estimation error

Subjects: Microsensors; Microsensors and nanosensors; Signal processing theory; Algebra; Time-varying control systems; Algebra; Optimisation techniques; MEMS and NEMS device technology; Optimal control; Discrete control systems; Other topics in statistics; Other topics in statistics

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