ABSTRACT
This chapter investigates the H∞ state estimation problem for a class of discrete-time complex networks with randomly occurring phenomena. The proposed randomly occurring phenomena include both probabilistic missing measurements and randomly occurring coupling delays, which are described by two random variable sequences satisfying individual probability distributions, respectively. Rather than the common Lipschitz-type function, a more general sector-like nonlinear function is employed to characterize the nonlinearities in the networks. By constructing a novel Lyapunov–Krasovskii functional and utilizing convex optimization method as well as Kronecker product, the chapter derives the sufficient conditions under which the desired state estimator exists. By employing the Lyapunov stability theory and convex program method, some sufficient conditions are derived and the design scheme of the estimator gains is derived. The chapter presents the numerical example to demonstrate the effectiveness of the results achieved.
