Robust weighted H_∞ filtering for networked systems with intermittent measurements of multiple sensors

Abstract

In this paper, we investigate the robust weighted H ∞ filtering problem for networked systems with intermittent measurements under the discrete-time framework. Multiple outputs of the plant are measured by separate sensors, each of which has a specific failure rate. Network-induced delay, packet dropouts and network-induced disorder phenomena are all incorporated in the modeling of the network link. The resulting closed-loop system involves both delayed noise and non-delayed noise. In order to make full use of the delayed information, we define a weighted H ∞ performance index. Sufficient delay-dependent and parameter-dependent conditions for the existence of the filter and the solvability of the addressed problem are given via a set of linear matrix inequalities. Two simulation examples are presented to illustrate the relationship between the minimal performance level and the weighting factor, which show the effectiveness of the proposed method.

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