Title
New distributed adaptive protocols for uncertain nonlinear leader-follower multi-agent systems via a repetitive learning control approach.
Abstract
In this paper, the distributed consensus problem of leader-follower multi-agent systems with unknown time-varying coupling gains and parameter uncertainties are investigated, and the fully distributed protocols with the adaptive updating laws of periodic time-varying parameters are designed by using a repetitive learning control approach. By virtue of algebraic graph theory, Barbalat’s lemma and an appropriate Lyapunov-Krasovskii functional, it is shown that each follower agent can asymptotically track the leader even though the dynamic of the leader is unknown to any of them, i.e., the global asymptotic consensus can be achieved. At last, a simulation example is given to illustrate the feasibility and efficiency of the proposed protocols.
Year
DOI
Venue
2019
10.1016/j.jfranklin.2019.01.052
Journal of the Franklin Institute
Field
DocType
Volume
Consensus,Mathematical optimization,Coupling,Nonlinear system,Leader follower,Control theory,Multi-agent system,Algebraic graph theory,Periodic graph (geometry),Lemma (mathematics),Mathematics
Journal
356
Issue
ISSN
Citations 
12
0016-0032
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Nana Yang111.71
Jun-Min LI239036.09