Distributed consensus-based estimation with unknown inputs and random link failures

被引：20

作者：

Yu, Dongdong ^{[1
]}

Xia, Yuanqing ^{[1
]}

Li, Li ^{[2
]}

Zhu, Cui ^{[3
]}

机构：

[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

[2] Yanshan Univ, Sch Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China

[3] Beijing Informat Sci & Technol Univ, Sch Informat & Commun Engn, Beijing 100101, Peoples R China

来源：

AUTOMATICA | 2020年 / 122卷

基金：

北京市自然科学基金; 中国国家自然科学基金;

关键词：

Distributed consensus-based estimation; Sensor networks; Unknown inputs; Random link failures;

D O I：

10.1016/j.automatica.2020.109259

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 distributed state estimation problem for linear time-varying systems with unknown exogenous inputs and random link failures. The unknown inputs appear both in the system equation and the measurement equation, and no information of them is available. The communication links between sensor nodes are unreliable and suffer from random link failures governed by a set of independent Bernoulli processes. By modeling the unknown inputs as processes with non-informative priors, a novel minimum mean square error (MMSE) estimator is derived. Then, a distributed consensus-based estimation algorithm is developed by repeatedly fusing local information from the neighbors possessing the successful link communications, in the sense that each sensor exchanges the local information obtained by performing the local MMSE estimation with its neighbors. Further, sufficient conditions are given to guarantee the stability of the proposed distributed estimator, in which the estimation error in each sensor is uniformly bounded in mean square. Finally, numerical examples are provided to show the effectiveness of the proposed technique. (c) 2020 Elsevier Ltd. All rights reserved.

引用

页数：9

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