Probability-guaranteed H∞ finite-horizon filtering for a class of nonlinear networked control systems with multiple missing measurements

In this paper, the problem of probability-guaranteed H_∞ finite-horizon filtering is studied for a class of nonlinear time-varying networked control systems (NCSs) with the effects of state delays and multiple missing measurements. The system matrices are governed by mutually independent stochastic variables subject to uniform distributions. The missing measurements phenomena of each sensor is modeled as a mutually independent stochastic variable satisfying certain probabilistic distribution. By augmenting the states of the original system and the constructed time-varying filter, the resulting system is converted into an H_∞ finite-horizon filtering problem. Sufficient conditions for the existence of the designed time-varying filter are obtained in terms of a set of linear matrix inequalities (LMIs), guaranteeing that the probability performance constraint and the H_∞ attenuation level are satisfied, simultaneously. At last, a recursive algorithm is presented to seek the time-varying filter parameters.