H∞ filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation.

This paper is concerned with the H∞ filtering problem for a class of networked systems subject to randomly occurring distributed state delays, nonlinearities, sensor saturation as well as missing measurements via unreliable communication channels. The output measurements are affected by sensor saturation which is described by sector-nonlinearities. The missing measurement is modeled as a linear random variable satisfying the Bernoulli distribution, and the nonlinearities with the form of global Lipschitz cover the well-known nonlinear functions. The purpose of the addressed problem is to design a full-order filter such that, in the simultaneous presence of distributed delays, randomly occurring nonlinearities, sensor saturation and missing measurements, the filtering dynamic system is guaranteed to be exponentially mean-square stable, and the H∞ filtering performance index is achieved. A sufficient condition for the solution of the addressed problem is derived, and the explicit expression of the desired filter gains is described in terms of the solution to linear matrix inequality (LMI). Finally, a numerical example is provided to show the effectiveness of the designed method.