Open AccessSampled‐data leader–follower algorithm for flocking of multi‐agent systems
Author(s) -
Yazdani Sahar,
Haeri Mohammad,
Su Housheng
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.5533
Subject(s) - flocking (texture) , upper and lower bounds , collision , computer science , control theory (sociology) , multi agent system , convergence (economics) , mathematical optimization , algorithm , mathematics , artificial intelligence , materials science , control (management) , composite material , mathematical analysis , computer security , economics , economic growth
In this study, the authors propose a new algorithm for the flocking problem of multi‐agent systems with the dynamic virtual leader under the sampled‐data frameworks. A necessary time‐varying condition is derived on the sampling period for preserving connectivity of the network and avoiding collision among agents. Then, defining a new energy function, it is proved that using a connectivity‐preserving potential function and under the sampling period which satisfies the necessary condition, an asymptotic flocking motion is achievable. Under the proposed sampled‐data flocking algorithm, the connectivity preservation of the network and collision avoidance among agents are guaranteed as well as the velocity convergence of all agents to that of the virtual leader is ensured. Moreover, employing the upper bound of the energy function, they specify an upper bound of the sampling period which could satisfy the time‐varying necessary condition. Finally, they present a numerical simulation to illustrate the theoretical results.