Event-triggered UKF for nonlinear dynamic systems with packet dropout

In this paper, the event-triggered nonlinear filtering problem is investigated for nonlinear dynamic systems over a wireless sensor network with packet dropout. Measurements are transmitted to a remote estimator only when a specific event happens for a reduction of communication cost. An event-triggered unscented Kalman filter related to trigger threshold is derived. It is shown that the prediction error covariance of the proposed filter is bounded and converges to a steady value if the threshold and packet dropout rate are small enough. Sufficient conditions are obtained to ensure stochastic stability of the filter, where a critical value of the threshold exists. Two examples are given to illustrate the effectiveness of the proposed filter.