Distributed stubborn‐set‐membership filtering with a dynamic event‐based scheme: The Takagi‐Sugeno fuzzy framework

Abstract

SummaryThe article develops a novel stubborn set‐membership filtering with the dynamic event‐triggered scheme for discrete‐time nonlinear systems with the state‐delays, unknown‐but‐bounded noises as well as abnormal measurements. First, in comparison with traditional event schemes, a dynamic event‐triggered scheme with a time‐varying auxiliary offset variable in the threshold is employed to schedule the access token with the purpose of mitigating the communication burden. A novel fuzzy stubborn filter in a distributed way is then constructed to obtain the ellipsoid set including the real state while constraining the direct influence of abnormal measurements, which could come from outliers or a malicious modification by attackers. An algorithm with the form of recursive linear matrix inequalities is presented to determine the desired ellipsoids as well as the distributed filter gains, where the operation of the algorithm do not depend on the global information of network topology. Finally, the validity of the proposed scheme is illustrated via an inverted pendulum system.