Event-triggered state estimation for a class of nonlinear stochastic systems with mixed time delays

In this paper, the state estimation problem is investigated for a class of nonlinear stochastic systems with mixed time delays under event-triggered scheme. Based on the proposed event-triggered scheme, the new measurement is sampled and then transmitted to the estimator only when the difference between the current measurement and the previous transmitted measurement is greater than a fixed threshold, thereby reducing the network traffic. Attention is focused on the design problem of the estimator such that the estimation error in mean square is bounded and then minimized. A novel Lyapunov function is employed to derive sufficient condition for the existence of the desired state estimators whose gain matrix can be computed by solving a convex problem. The gain matrix of the estimator is characterized in order that an asymptotic bound of the estimation error is found and subsequently minimized. A numerical simulation is provided to illustrate the effectiveness of the results.