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η(t)-consensus of multi-agent systems with directed graphs via event-triggered principles.

Authors :
Lin, Zongzong
Lu, Wenlian
Chen, Tianping
Source :
Neurocomputing. Apr2019, Vol. 339, p1-9. 9p.
Publication Year :
2019

Abstract

Abstract In this paper, we investigate η (t)-consensus problem of the multi-agent system with directed graph via event-triggered principles. The η (t)-consensus is defined as the difference between agents' states less than a certain preassigned time-dependent bound function η (t). This concept can be regarded as a generalization of the existing concepts such as quasi-consensus/synchronization, where the state differences are requested below a certain constant bound, and exponential synchronization, where the state differences converge to zero exponentially, and more generally, μ -consensus, where the state differences converge to zero with diverse convergence ratios and patterns. The event-triggering principles are asynchronous for each agent and rely on the bound function η (t), as well as its derivative, the agent's own state information and some algebraic information of the network, to determine the next trigger time. We prove that with a loose assumption of the bound function, if the graph is strongly connected graph or generally possesses a spanning tree, then the proposed principles realize η (t)-consensus of the multi-agent system, and moreover, the Zeno behavior is excluded. We give several numerical examples to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
339
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
135351469
Full Text :
https://doi.org/10.1016/j.neucom.2019.01.061