State Estimation for Discrete-Time Complex Dynamical Networks with Markovian Packet Losses

Abstract

In this paper, the state estimation problem is investigated for discrete-time output coupled complex networks with Markovian packet losses. Unlike the majority of emerging research on state estimation with Bernoulli packet dropout, the Markov chain is used to describe the random packet losses. In use of the Lyapunov functional theory and stochastic analysis method, the explicit description of the estimator gains is presented in the form of the solution to certain linear matrix inequalities (LMIs). At last, simulations are exploited to illustrate the proposed estimator design scheme is applicable.