H∞ state estimation for time-varying networks with probabilistic delay in measurements

This paper is concerned with the H∞ state estimation problem for the time-varying networks with probabilistic delay over a finite horizon. The measurements for the proposed network experience randomly occurring delays (RODs) with changeable probabilities, which could be described by a time-varying Bernoulli distribution stochastic sequence. Stochastic analysis and probability-dependent method are utilized to develop sufficient criteria under which the prescribed H∞ performance can be achieved. It is worth mentioning that, based on the available lower and upper bounds of the varying probabilities, the target estimator gains are transformed into a convex optimization problem subjecting to a set of recursive matrix inequalities which can be applied in a more robust situation. Finally, a simulation example is provided to show the effectiveness of the obtained results.