Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach
This paper is concerned with the distributed filtering problem for a class of delayed nonlinear systems with random sensor saturation (RSS) under a dynamic event-triggered mechanism. The nonlinear function is assumed to satisfy the Lipschitz condition. A dynamic event-triggered mechanism is employed...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2021-01-01
|
Series: | Systems Science & Control Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/21642583.2021.1919935 |
id |
doaj-1df148c014074cdeba4feca65db6df30 |
---|---|
record_format |
Article |
spelling |
doaj-1df148c014074cdeba4feca65db6df302021-06-02T08:43:39ZengTaylor & Francis GroupSystems Science & Control Engineering2164-25832021-01-019144045410.1080/21642583.2021.19199351919935Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approachZehao Li0Jun Hu1Jiaxing Li2Harbin University of Science and TechnologyHarbin University of Science and TechnologyHarbin University of Science and TechnologyThis paper is concerned with the distributed filtering problem for a class of delayed nonlinear systems with random sensor saturation (RSS) under a dynamic event-triggered mechanism. The nonlinear function is assumed to satisfy the Lipschitz condition. A dynamic event-triggered mechanism is employed to further reduce the innovation transmission frequencies among the adjacent nodes. Both the Bernoulli distributed random variables and saturation function are employed to model the phenomenon of RSS. The aim of this paper is to design a sub-optimal filter such that the covariance of the filtering error has an upper bound, which is minimized by appropriately computing the filter gain. Furthermore, the error boundedness is analysed and a sufficient criterion is presented to ensure that the filtering error is mean-square bounded. Finally, a numerical example is provided to verify the effectiveness of the proposed filtering algorithm.http://dx.doi.org/10.1080/21642583.2021.1919935nonlinear delayed systemdynamic event-triggered mechanismdistributed filteringrss |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zehao Li Jun Hu Jiaxing Li |
spellingShingle |
Zehao Li Jun Hu Jiaxing Li Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach Systems Science & Control Engineering nonlinear delayed system dynamic event-triggered mechanism distributed filtering rss |
author_facet |
Zehao Li Jun Hu Jiaxing Li |
author_sort |
Zehao Li |
title |
Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
title_short |
Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
title_full |
Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
title_fullStr |
Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
title_full_unstemmed |
Distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
title_sort |
distributed filtering for delayed nonlinear system with random sensor saturation: a dynamic event-triggered approach |
publisher |
Taylor & Francis Group |
series |
Systems Science & Control Engineering |
issn |
2164-2583 |
publishDate |
2021-01-01 |
description |
This paper is concerned with the distributed filtering problem for a class of delayed nonlinear systems with random sensor saturation (RSS) under a dynamic event-triggered mechanism. The nonlinear function is assumed to satisfy the Lipschitz condition. A dynamic event-triggered mechanism is employed to further reduce the innovation transmission frequencies among the adjacent nodes. Both the Bernoulli distributed random variables and saturation function are employed to model the phenomenon of RSS. The aim of this paper is to design a sub-optimal filter such that the covariance of the filtering error has an upper bound, which is minimized by appropriately computing the filter gain. Furthermore, the error boundedness is analysed and a sufficient criterion is presented to ensure that the filtering error is mean-square bounded. Finally, a numerical example is provided to verify the effectiveness of the proposed filtering algorithm. |
topic |
nonlinear delayed system dynamic event-triggered mechanism distributed filtering rss |
url |
http://dx.doi.org/10.1080/21642583.2021.1919935 |
work_keys_str_mv |
AT zehaoli distributedfilteringfordelayednonlinearsystemwithrandomsensorsaturationadynamiceventtriggeredapproach AT junhu distributedfilteringfordelayednonlinearsystemwithrandomsensorsaturationadynamiceventtriggeredapproach AT jiaxingli distributedfilteringfordelayednonlinearsystemwithrandomsensorsaturationadynamiceventtriggeredapproach |
_version_ |
1721406321440325632 |