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Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks
The state observer for dynamic links in complex dynamical networks (CDNs) is investigated by using the adaptive method whether the networks are undirected or directed. In this paper, a complete network model is proposed, which is composed of two coupled subsystems called nodes subsystem and links su...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609145/ https://www.ncbi.nlm.nih.gov/pubmed/33178260 http://dx.doi.org/10.1155/2020/8846438 |
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author | Gao, Zilin Xiong, Jiang Zhong, Jing Liu, Fuming Liu, Qingshan |
author_facet | Gao, Zilin Xiong, Jiang Zhong, Jing Liu, Fuming Liu, Qingshan |
author_sort | Gao, Zilin |
collection | PubMed |
description | The state observer for dynamic links in complex dynamical networks (CDNs) is investigated by using the adaptive method whether the networks are undirected or directed. In this paper, a complete network model is proposed, which is composed of two coupled subsystems called nodes subsystem and links subsystem, respectively. Especially, for the links subsystem, associated with some assumptions, the state observer with parameter adaptive law is designed. Compared to the existing results about the state observer design of CDNs, the advantage of this method is that a estimation problem of dynamic links is solved in directed networks for the first time. Finally, the results obtained in this paper are demonstrated by performing a numerical example. |
format | Online Article Text |
id | pubmed-7609145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-76091452020-11-10 Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks Gao, Zilin Xiong, Jiang Zhong, Jing Liu, Fuming Liu, Qingshan Comput Intell Neurosci Research Article The state observer for dynamic links in complex dynamical networks (CDNs) is investigated by using the adaptive method whether the networks are undirected or directed. In this paper, a complete network model is proposed, which is composed of two coupled subsystems called nodes subsystem and links subsystem, respectively. Especially, for the links subsystem, associated with some assumptions, the state observer with parameter adaptive law is designed. Compared to the existing results about the state observer design of CDNs, the advantage of this method is that a estimation problem of dynamic links is solved in directed networks for the first time. Finally, the results obtained in this paper are demonstrated by performing a numerical example. Hindawi 2020-10-21 /pmc/articles/PMC7609145/ /pubmed/33178260 http://dx.doi.org/10.1155/2020/8846438 Text en Copyright © 2020 Zilin Gao et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gao, Zilin Xiong, Jiang Zhong, Jing Liu, Fuming Liu, Qingshan Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title | Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title_full | Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title_fullStr | Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title_full_unstemmed | Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title_short | Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks |
title_sort | adaptive state observer design for dynamic links in complex dynamical networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609145/ https://www.ncbi.nlm.nih.gov/pubmed/33178260 http://dx.doi.org/10.1155/2020/8846438 |
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