Robust Kalman Filtering For Descriptor Systems With Unstructured Uncertainties

A robust Kalman-type recursive filter has been proposed for descriptor systems subject to linear unstructured additive uncertainties in this paper. It is proved that the linear additive uncertainties during filtering can be represented by the intersection of a series of additive uncertainties relying on the actual plant. A set of additive uncertainties independent of the actual states is utilized in this paper to include this intersection, whose parameters can be obtained offline through convex optimizations. A numerical simulation shows that the algorithm can be realized recursively for linear additive uncertain- ties, and verifies the effectiveness of the proposed algorithm.