H∞ filtering for networked systems with random sensor delays, packet dropouts and missing measurements

In this paper, an H_¿ filter design problem is studied for networked stochastic linear discrete-time systems with mixed uncertainties of random measurement delays, packet dropouts and missing measurements. We model the packet delivery characteristics of the network as a four-state Markov process and note that the results for discrete-time linear systems with Markovian jumping parameters can be applied. We focus on the design problem of a full-order H_¿ filter such that for all possible uncertain measurements the filtering error dynamics is exponentially mean square stable and a prescribed H_¿ performance bound is guaranteed. Necessary and sufficient bilinear matrix inequality (BMI) condition for the synthesis of the aforementioned filter for a discrete-time jump system is presented. Some simulation examples are presented to show the applicability and effectiveness of the proposed approach.