Event-triggered nonlinear consensus in directed multi-agent systems with combinational state measurements

Huaqing Li, Guo Chen and Li Xiao

International Journal of Systems Science, 2016, vol. 47, issue 14, 3364-3377

Abstract: Event-triggered sampling control is motivated by the applications of embedded microprocessors equipped in the agents with limited computation and storage resources. This paper studied global consensus in multi-agent systems with inherent nonlinear dynamics on general directed networks using decentralised event-triggered strategy. For each agent, the controller updates are event-based and only triggered at its own event times by only utilising the locally current sampling data. A high-performance sampling event that only needs local neighbours’ states at their own discrete time instants is presented. Furthermore, we introduce two kinds of general algebraic connectivity for strongly connected networks and strongly connected components of the directed network containing a spanning tree so as to describe the system's ability for reaching consensus. A detailed theoretical analysis on consensus is performed and two criteria are derived by virtue of algebraic graph theory, matrix theory and Lyapunov control approach. It is shown that the Zeno behaviour of triggering time sequence is excluded during the system's whole working process. A numerical simulation is given to show the effectiveness of the theoretical results.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2016.1146973 (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:47:y:2016:i:14:p:3364-3377

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

DOI: 10.1080/00207721.2016.1146973

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 ().