Quantized H∞ filtering for discrete-time networked systems with mixed delays and missing measurements

In this paper, the H∞ filtering problem is investigated for networked systems subject to quantization, discrete and distributed delays as well as missing measurements over unreliable communication channel. The missing measurements are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution, while the quantized measured output signals are considered by using the logarithmic quantization. The purpose of this paper is to design a filter such that, for the mixed delays and unreliable communication channel, the filtering error system is asymptotically mean square stable, and the H∞ filtering performance index is satisfied. A sufficient condition for the solvability of the problem is derived, and the filter parameters are designed by solving a linear matrix inequality (LMI). Finally, a numerical example is illustrated to show the usefulness of the designed filtering method.