Event-triggered approach for finite-time state estimation of delayed complex dynamical networks with random parameters

This article emphasizes the finite-time state estimation problem for delayed complex dynamical networks with random parameters. In order to reduce the amount of transmission process, an aperiodic sampled-data event-triggered mechanism is introduced to determine whether the measurement output should be released at certain time points which incorporate an appropriate triggering condition and sampling moments. Furthermore, a concept of finite-time boundedness in thepth moment is proposed to access the performance of state estimator. The objective of this article is to design an event-triggered state estimator to estimate the states of nodes such that, in the presence of time delays, uncertainties, and randomly changing coupling weights, the estimation error system is finite-time bounded in thepth moment related to a given constant. Some sufficient conditions in form of linear matrix inequalities and algebraic inequalities are established to guarantee finite-time boundedness. Finally, a numerical example is presented to show the effectiveness of the theoretical results.