Event-triggered nonlinear filtering for networked systems with correlated noises

被引:13
作者
Li, Li [1 ]
Niu, Mengfei [1 ]
Yang, Hongjiu [1 ]
Liu, Zhixin [1 ]
机构
[1] Yanshan Univ, Sch Elect Engn, Qinhuangdao 066004, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2018年 / 355卷 / 13期
基金
中国国家自然科学基金;
关键词
STATE ESTIMATION; KALMAN FILTER; COMMUNICATION; PERFORMANCE; FUSION; DELAYS; TIME;
D O I
10.1016/j.jfranklin.2018.05.044
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:5811 / 5829
页数:19
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