Event-triggered nonlinear filtering for networked systems with correlated noises

This paper focuses on the filtering problem for nonlinear networked systems with event-triggered data transmission and correlated noises. An event-triggered data transmission mechanism is introduced to reduce excessive measurements transmitted over a bandwidth-constrained network. Considering that process noise and measurement noise are one-step cross-correlated, an UKF-based filtering algorithm which depends on correlation parameter and trigger threshold is presented. Then sufficient conditions are established to ensure stability of the designed filter, where a critical value of the correlation parameter exists. Finally, the effectiveness of the proposed filtering algorithm is demonstrated by comparative simulations. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.