Event-Triggered State Estimation for Complex Systems with Randomly Nonlinearities and Time-Varying Delay

The event-triggered state estimation is investigated for a class of complex networks system with randomly nonlinearities. A novel event-triggered scheme is proposed, which can reduce the information communication burden in the network. Considering the effect of transmission delay, a time-varying delayed system model is constructed. Attention of this paper is focused on the analysis and design of a reliable estimator for the complex networks through the available output measurements under event-triggered scheme. In order to design the state estimator, a Lyapunov functional approach and the linear matrix inequality technique are employed. A sufficient condition is obtained in which the estimator error dynamics is exponential asymptotically stable, and a state estimator of considered complex networks can be achieved by solving some linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

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