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DC Field | Value | Language |
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dc.contributor.author | Gao, M | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Sheng, L | - |
dc.contributor.author | Zou, L | - |
dc.contributor.author | Liu, H | - |
dc.date.accessioned | 2023-06-17T18:26:23Z | - |
dc.date.available | 2023-06-17T18:26:23Z | - |
dc.date.issued | 2022-01-11 | - |
dc.identifier | ORCID iD: Zidong Wang https://orcid.org/0000-0002-9576-7401 | - |
dc.identifier.citation | Gao, M. et al. (2022) 'Centralized moving-horizon estimation for a class of nonlinear dynamical complex networks under event-triggered transmission scheme', International Journal of Robust and Nonlinear Control, 2022, 32 (6), pp. 3872 - 3889. doi: 10.1002/rnc.6000. | en_US |
dc.identifier.issn | 1049-8923 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/26671 | - |
dc.description | Data availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. | en_US |
dc.description.abstract | This article is concerned with the problem of event-triggered centralized moving-horizon state estimation for a class of nonlinear dynamical complex networks. An event-triggered scheme is employed to reduce unnecessary data transmissions between sensors and estimators, where the signal is transmitted only when certain condition is violated. By treating sector-bounded nonlinearities as certain sector-bounded uncertainties, the addressed centralized moving-horizon estimation problem is transformed into a regularized robust least-squares problem that can be effectively solved via existing convex optimization algorithms. Moreover, a sufficient condition is derived to guarantee the exponentially ultimate boundedness of the estimation error, and an upper bound of the estimation error is also presented. Finally, a numerical example is provided to demonstrate the feasibility and efficiency of the proposed estimator design method. | en_US |
dc.description.sponsorship | National Natural Science Foundation of China. Grant Numbers: 61873148, 61933007, 62033008, 62073339, 62173343; Natural Science Foundation of Shandong Province of China. Grant Number: ZR2020YQ49; AHPU Youth Top-notch Talent Support Program of China. Grant Number: 2018BJRC009; Natural Science Foundation of Anhui Province of China. Grant Number: 2108085MA07; China Postdoctoral Science Foundation. Grant Number: 2018T110702; Postdoctoral Special Innovation Foundation of Shandong Province of China. Grant Number: 201701015; Royal Society of the UK; Alexander von Humboldt Foundation of Germany. | en_US |
dc.format.extent | 3872 - 3889 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Wiley | en_US |
dc.rights | Copyright © 2022 John Wiley & Sons Ltd. All Rights Reserved. This is the peer reviewed version of the following article: Centralized moving-horizon estimation for a class of nonlinear dynamical complex networks under event-triggered transmission scheme, which has been published in final form at https://doi.org/10.1002/rnc.6000. This article may be used for non-commercial purposes in accordance with John Wiley & Sons Ltd's Terms and Conditions for Self-Archiving (see: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html). | - |
dc.rights.uri | https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html | - |
dc.subject | bounded estimation error | en_US |
dc.subject | centralized moving-horizon estimation | en_US |
dc.subject | dynamical complex networks | en_US |
dc.subject | event-triggered mechanism | en_US |
dc.subject | sector-bounded nonlinearity | en_US |
dc.title | Centralized moving-horizon estimation for a class of nonlinear dynamical complex networks under event-triggered transmission scheme | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1002/rnc.6000 | - |
dc.relation.isPartOf | International Journal of Robust and Nonlinear Control | - |
pubs.issue | 6 | - |
pubs.publication-status | Published | - |
pubs.volume | 32 | - |
dc.identifier.eissn | 1099-1239 | - |
dc.rights.holder | John Wiley & Sons Ltd | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © 2022 John Wiley & Sons Ltd. All Rights Reserved. This is the peer reviewed version of the following article: Centralized moving-horizon estimation for a class of nonlinear dynamical complex networks under event-triggered transmission scheme, which has been published in final form at https://doi.org/10.1002/rnc.6000. This article may be used for non-commercial purposes in accordance with John Wiley & Sons Ltd's Terms and Conditions for Self-Archiving (see: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html). | 196.17 kB | Adobe PDF | View/Open |
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