Robust ℋ∞ filtering in sensor networks with uncertain rates of packet losses

The paper is concerned with the robust ℋ_∞ filtering problem in sensor networks with uncertain rates of packet losses. The packet losses occurring 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 to ensure 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), 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.