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Robust state and fault estimation for linear descriptor stochastic systems with disturbances: a DC motor application

Robust state and fault estimation for linear descriptor stochastic systems with disturbances: a DC motor application

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This study considers the problem of simultaneously estimating the state and the fault of an uncertain direct current (DC) motor in light of the unknown input filtering framework. The objective is to derive an optimal filter in order to achieve a robust descriptor state and fault estimation in the presence of parameter uncertainties. To achieve the aim, the uncertain descriptor system with faults is first transformed into an equivalent standard state-space system with faults and unknown inputs. Then, it is shown that the previously proposed robust two-stage Kalman filter can be applied to yield the optimal robust state and fault estimator, which is free of the unknown inputs. Finally, a direct application to DC motor is included to show the effectiveness of the proposed optimal robust filter.

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