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In this paper, the problem of fault estimation is considered for a class of time-varying systems through a sensor network. The measurements collected via the sensor network are subject to probabilistic data missing. A set of least square estimators are designed for the addressed systems such that the estimation error variance is minimized at each tim step. By solving a set of Riccati-like matrix equations,...
This paper addresses the fault detection problem for discrete-time Markovian jump systems with incomplete knowledge of transition probabilities, randomly varying nonlinearities and sensor saturations. An optimized fault detection filter is designed such that 1) the fault detection dynamics is stochastically stable; 2) the effect from the exogenous disturbance on the residual is attenuated with respect...
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