Distributed resilient state estimation over sensor networks with random nonlinearities, fading measurements, and stochastic gain variations

Abstract

AbstractThe distributed resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under consideration involves three phenomena of incomplete information: randomly occurring nonlinearities, fading measurements, and random gain variations. The probabilistic characteristics of the above phenomena are depicted by three sets of independent random variables subject to more general random distribution. Based on the above model, by applying Lyapunov functional approach and random distribution solution method, the asymptotic stability in the mean square sense of the estimation error system with a given attenuation level is proved. Further, the estimator parameters are solved by introducing a novel linearization method. Finally, a numerical simulation is given to illustrate the validity of the theoretical results.