H∞ filtering for uncertain time-varying systems with multiple randomly occurred nonlinearities and successive packet dropouts

This paper is concerned with the robust H-infinity finite-horizon filtering problem for discrete time-varying stochastic systems with multiple randomly occurred sector-nonlinearities (MROSNs) and successive packet dropouts. MROSNs are proposed to model a class of sector-like nonlinearities that occur according to the multiple Bernoulli distributed white sequences with a known conditional probability. Different from traditional approaches, in this paper, a time-varying filter is designed directly for the addressed system without resorting to the augmentation of system states and measurement, which helps reduce the filter order. A new H-infinity filtering technique is developed by means of a set of recursive linear matrix inequalities that depend on not only the current available state estimate but also the previous measurement, therefore ensuring a better accuracy. Finally, two illustrative examples are used to demonstrate the effectiveness and applicability of the proposed filter design scheme. Copyright (C) 2010 John Wiley & Sons, Ltd.