Event‐triggered UKF for nonlinear dynamic systems with packet dropout

Summary 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.