Adaptive leaderless consensus of agents in jointly connected networks
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Date
Authors
Yu, Hui
Xia, Xiaohua
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
In this paper, the leaderless consensus problem of multi-agent systems with
jointly connected topologies and nonlinear dynamics is considered, in which
the nonlinear dynamics are assumed to be non-identical and unknown. The
unknown nonlinear dynamics existing in the systems are assumed to be linearly
parameterized, and an adaptive design method for leaderless multiagent
systems is presented. By just using the relative position information
between each agent and its neighbours, a distributed adaptive consensus control
algorithm for the considered systems is proposed, in which the network
graphs are jointly connected. Both the global uniform asymptotical stability
and the global uniform asymptotical parameter convergence analysis of the
adaptive control algorithm are carried out by using adaptive control theory,
Lyapunov theory and algebraic graph theory. Finally, an example is given to
illustrate the validity of our theoretical results.
Description
Keywords
Adaptive consensus, Decentralized control, Parameter convergence, Jointly connected topology, Multi-agent system
Sustainable Development Goals
Citation
Yu, H & Xia, XH 2017, 'Adaptive leaderless consensus of agents in jointly connected networks', Neurocomputing, vol. 241, pp. 64-70.