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Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach. / Qu, Xiaojun; Chen, Yangzhou; Aleksandrov, A. Yu; Dai, Guiping.

In: Neurocomputing, Vol. 222, 26.01.2017, p. 54-61.

Research output: Contribution to journal › Article › peer-review

Harvard

Qu, X, Chen, Y, Aleksandrov, AY & Dai, G 2017, 'Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach', Neurocomputing, vol. 222, pp. 54-61. https://doi.org/10.1016/j.neucom.2016.10.011

APA

Qu, X., Chen, Y., Aleksandrov, A. Y., & Dai, G. (2017). Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach. Neurocomputing, 222, 54-61. https://doi.org/10.1016/j.neucom.2016.10.011

Vancouver

Qu X, Chen Y, Aleksandrov AY, Dai G. Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach. Neurocomputing. 2017 Jan 26;222:54-61. https://doi.org/10.1016/j.neucom.2016.10.011

Author

Qu, Xiaojun ; Chen, Yangzhou ; Aleksandrov, A. Yu ; Dai, Guiping. / Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach. In: Neurocomputing. 2017 ; Vol. 222. pp. 54-61.

BibTeX

@article{09c41804dc164337976915f6f5af3428,
title = "Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach",
abstract = "This paper investigates the consensus problem of large-scale multi-agent systems (MASs) with a directed communication topology, especially for the MAS whose topology contains small strongly connected components. A sufficient and necessary consensus criterion is proposed through the combination of two methods. Firstly, a communication searching algorithm is utilized to make sure that each agent obtains the local topology information of strongly connected component where it is located. Secondly, a state-linear-transformation decomposes the consensus problem into a group of stability problems based on the strongly connected components. The corresponding consensus criterion reduces the computational complexity. Moreover, according to the consensus criterion, a distributed design procedure of gain matrices is proposed based on the homotopy method.",
keywords = "Consensus, Multi-agent systems, Partial stability, State-linear-transformation",
author = "Xiaojun Qu and Yangzhou Chen and Aleksandrov, {A. Yu} and Guiping Dai",
year = "2017",
month = jan,
day = "26",
doi = "10.1016/j.neucom.2016.10.011",
language = "English",
volume = "222",
pages = "54--61",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Distributed consensus of large-scale multi-agent systems via linear-transformation-based partial stability approach

AU - Qu, Xiaojun

AU - Chen, Yangzhou

AU - Aleksandrov, A. Yu

AU - Dai, Guiping

PY - 2017/1/26

Y1 - 2017/1/26

N2 - This paper investigates the consensus problem of large-scale multi-agent systems (MASs) with a directed communication topology, especially for the MAS whose topology contains small strongly connected components. A sufficient and necessary consensus criterion is proposed through the combination of two methods. Firstly, a communication searching algorithm is utilized to make sure that each agent obtains the local topology information of strongly connected component where it is located. Secondly, a state-linear-transformation decomposes the consensus problem into a group of stability problems based on the strongly connected components. The corresponding consensus criterion reduces the computational complexity. Moreover, according to the consensus criterion, a distributed design procedure of gain matrices is proposed based on the homotopy method.

AB - This paper investigates the consensus problem of large-scale multi-agent systems (MASs) with a directed communication topology, especially for the MAS whose topology contains small strongly connected components. A sufficient and necessary consensus criterion is proposed through the combination of two methods. Firstly, a communication searching algorithm is utilized to make sure that each agent obtains the local topology information of strongly connected component where it is located. Secondly, a state-linear-transformation decomposes the consensus problem into a group of stability problems based on the strongly connected components. The corresponding consensus criterion reduces the computational complexity. Moreover, according to the consensus criterion, a distributed design procedure of gain matrices is proposed based on the homotopy method.

KW - Consensus

KW - Multi-agent systems

KW - Partial stability

KW - State-linear-transformation

UR - http://www.scopus.com/inward/record.url?scp=84997272306&partnerID=8YFLogxK

U2 - 10.1016/j.neucom.2016.10.011

DO - 10.1016/j.neucom.2016.10.011

M3 - Article

AN - SCOPUS:84997272306

VL - 222

SP - 54

EP - 61

JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

ER -

ID: 29125349