Distributed State Estimation for Complex Networks With Delayed Measurements

被引：0
|
作者：
Teng D. [1 ]
Xu Y. [1 ]
Bao H. [1 ]
Wang Z. [2 ,3 ]
Lu R.-Q. [1 ]
机构：
[1] Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou
[2] Hangzhou Innovation Institute (Yuhang), Beihang University, Hangzhou
[3] School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2024年 / 50卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Complex network; delayed measurement; distributed state estimation; stability analysis;
D O I：
10.16383/j.aas.c210921
中图分类号：
学科分类号：
摘要：
This work addresses the distributed state estimation for complex networks with delayed measurements. The Bernoulli process is employed to describe the measurements with randomly occurred one step delay. The state predictor is derived based on the system mode, and the distributed state estimator is designed by using delayed measurements. The coupling term between nodes is eliminated based on Young＇s inequality, and the covariance of state prediction is improved by optimizing the parameters introduced by Young＇s inequality. Furthermore, the optimal state estimation error covariance is achieved by designing the estimator gain. Thanks to the state prediction error covariance, the iterative inequality of the state estimation error covariance is derived, and its sufficient condition for stability is established. Finally, the moving vehicles based coupled system is given to illustrate the effectiveness of the designed estimator. © 2024 Science Press. All rights reserved.
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页码：841 / 850
页数：9
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