Robust fault and state estimation for discrete time-varying uncertain systems
Résumé
In this paper, we consider the robust Kalman filtering for uncertain discrete time-varying systems, to solve the problem of simultaneously state and fault estimation. The system under consideration is subjected to time-varying norm-bounded parameter uncertainty in both the state and measurement matrices. The approach suggested rests on the use of the Augmented State Robust Kalman Filter (ASRKF) based on the optimization of an upper bound on the variance error of the state estimation. A necessary and sufficient condition for the existence of the filter is established in terms of a pair of Riccati equations. The proposed filter is tested by an illustrative example.