Dynamic Event-triggered State Estimation for Nonlinear Coupled Output Complex Networks Subject to Innovation Constraints

被引：3

作者：

Jun Hu ^{[1
,2
]}

Chaoqing Jia ^{[3
]}

Hui Yu ^{[3
]}

Hongjian Liu ^{[4
]}

机构：

[1] the Department of Applied Mathematics, Harbin University of Science and Technology

[2] the School of Automation, Harbin University of Science and Technology

[3] the Department of Applied Mathematics,Harbin University of Science and Technology

[4] the School of Mathematics and Physics, Anhui Polytechnic University

来源：

IEEE/CAAJournalofAutomaticaSinica | 2022年 / 9卷 / 05期

基金：

黑龙江省自然科学基金; 中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

O157.5 [图论];

学科分类号：

070104 ;

摘要：

Dear editor,This letter investigates the recursive state estimation (RSE)problem for a class of coupled output complex networks via the dynamic event-triggered communication mechanism (DETCM) and innovation constraints (ICs). Firstly, a DETCM is employed to regulate the transmission sequences. Then, in order to improve the reliability of network communication, a saturation function is introduced to constrain the measurement outliers.

引用

页码：941 / 944

页数：4

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (05) :1139-1151

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