Distributed H∞ filtering for a class of sensor networks with uncertain rates of packet losses

In this paper, the distributed H∞ filtering problem is discussed for a class of sensor networks with uncertain rates of packet losses. The packet losses occur randomly in measurements from local sensor and in transmission from the neighbor sensors are mutually independent but obey Bernoulli distribution. Different from the most results on packet losses, the rates of packet losses are assumed to be uncertain and norm-bounded. We aim to design a linear full-order filter such that the estimation error converges to zero asymptotically in the mean square while the disturbance rejection attenuation is constrained to a given level by means of the H∞ performance index. By using the parameter-dependent Lyapunov function method, the sufficient conditions are obtained for ensuring the stochastic stability as well as prescribed H∞ performance for the overall filtering error dynamics. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Finally, one simulation example is employed to demonstrate the effectiveness of the proposed filter design technique in this paper.