English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Group consensus for fractional-order heterogeneous multi-agent systems under cooperation-competition networks with time delays

Sun, F., Han, Y., Zhu, W., Kurths, J. (2024): Group consensus for fractional-order heterogeneous multi-agent systems under cooperation-competition networks with time delays. - Communications in Nonlinear Science and Numerical Simulation, 133, 107951.
https://doi.org/10.1016/j.cnsns.2024.107951

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Sun, Fenglan1, Author              
Han, Yunpeng2, Author
Zhu, Wei2, Author
Kurths, Jürgen1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: The issue of group consensus for heterogeneous fractional-order multi-agent systems under the cooperation-competition networks with time delays is investigated in this paper. Novel group consensus control protocols with input and communication delays are designed based on cooperative-competitive interaction. The considered multi-agent systems consists of fractional order dynamics with the single integrator and the double integrator, and the speed of agents is not known. The matrix theory, frequency domain approach and graph theory are used to figure out the sufficient conditions for group consensus under the switching and fixed topology, respectively. Finally, numerical simulation examples are given to verify the correctness of the theoretical results.

Details

show
hide
Language(s): eng - English
 Dates: 2024-03-082024-06-01
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.cnsns.2024.107951
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Communications in Nonlinear Science and Numerical Simulation
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 133 Sequence Number: 107951 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/201610061
Publisher: Elsevier