Observer-based event-triggered leader-following control of a class of linear multi-agent systems
Yang Yang,
Dong Yue and
Xiangpeng Xie
International Journal of Systems Science, 2018, vol. 49, issue 12, 2536-2547
Abstract:
This paper addresses an observer-based consensus problem for leader-following control of a class of linear multi-agent systems (MASs) under a directed communication topology via event-triggered approaches. State observers are employed to tackle the scenario wherein inner information of the follower agents are not available for measurement. And then, an observer-based distributed leader-following control scheme is developed on the basis of event-triggered mechanisms. Further, to avoid continuous measurement information monitor, we present a technical approach for generation of the combinational information from their own neighbouring agents only at triggered instants. In theory, the stability of the resulting closed-loop system is rigorously investigated, and it is proven that all signals in the closed-loop system are bounded and Zeno behaviour is also excluded. Finally, simulation examples are presented for illustration of the theoretical claims.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2018.1502833 (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:49:y:2018:i:12:p:2536-2547
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2018.1502833
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 ().