Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Mean-square consensus for heterogeneous multi-agent systems with probabilistic time delay

Sun, F., Liao, X., Kurths, J. (2021): Mean-square consensus for heterogeneous multi-agent systems with probabilistic time delay. - Information Sciences, 543, 112-124.
https://doi.org/10.1016/j.ins.2020.07.021

Item is

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Sun, Fenglan1, Autor              
Liao, Xiaogang2, Autor
Kurths, Jürgen1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: This paper studies the delay-dependent consensus problem of heterogeneous multi-agent systems over directed topology. The heterogeneous dynamics consisting of both first-order and second-order agents with random time delay are considered. New distributed control protocols based on the probability distribution of time delay are proposed for the leader-following and leaderless systems. By adopting matrix theory, Lyapunov-Krasovskii function and stochastic analysis, some less conservative conditions for the mean-square consensus are established over directed fixed topology and switching topologies. Moreover, the larger upper bounds of time delay are obtained. Finally, several simulations are presented to illustrate the obtained results.

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2020-07-232021-01-08
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.ins.2020.07.021
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
MDB-ID: No data to archive
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Working Group: Network- and machine-learning-based prediction of extreme events
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Information Sciences
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 543 Artikelnummer: - Start- / Endseite: 112 - 124 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/Information-Sciences
Publisher: Elsevier