Distributed robust adaptive flocking for uncertain nonlinear multi-agent systems with time-varying communication delay

Ali Izadipour, Jafar Ghaisari and Javad Askari

International Journal of Systems Science, 2020, vol. 51, issue 1, 72-86

Abstract: This paper is concerned with the flocking problem of networked multi-agent systems while considering the perturbed communication link, time-varying communication delay and perturbed nonlinear dynamics. The state information of agents is exchanged among agents through a delayed communication network with an unknown upper bound. The proposed algorithm doesn't require the precise value of the communication delay upper bound. In addition, it can be applied to the networks with different time delays in different links. In order to deal with the perturbation of communication links, a distributed adaptive controller is proposed. The controllers are designed using only the delayed velocity information of one-hop neighbour. By means of the Lyapunov–Krasovskii analysis, sufficient conditions on the upper bound of communication delay derivative are computed under which flocking will be achieved and all states are globally uniformly bounded. Simulation results illustrate the effectiveness of the proposed algorithm.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2019.1694196 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:51:y:2020:i:1:p:72-86

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2019.1694196

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().