Open AccessRegion tracking control for high‐order multi‐agent systems in restricted space
Author(s) -
Sun Xiaoming,
Sam Ge Shuzhi,
Zhang Jun,
Cao Xianbin
Publication year - 2016
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.2015.0877
Subject(s) - backstepping , control theory (sociology) , computer science , lyapunov function , artificial neural network , tracking error , neighbourhood (mathematics) , tracking (education) , obstacle , multi agent system , adaptive control , track (disk drive) , control (management) , mathematics , artificial intelligence , nonlinear system , psychology , pedagogy , operating system , mathematical analysis , physics , quantum mechanics , political science , law
In this study, decentralised region tracking control is proposed to force a group of mobile agents with high‐order non‐linear dynamics to track a moving target region without collisions as well as to avoid the obstacle on the track in restricted space. The decentralised controllers can also guarantee connectivity preserving of the dynamic interaction network. The control design is based on artificial potential functions, neural network (NN) approximation, adaptive backstepping techniques and Lyapunov's method. It is proved that under the adaptive NN control, the tracking error of each agent can converge to an adjustable neighbourhood of the origin, although some of them do not access the desired region directly. Simulation results are represented to illustrate the performance of the proposed approach.