TY - JOUR
T1 - Synchronised tracking control of multi-agent system with high-order dynamics
AU - Cui, R.
AU - Ren, B.
AU - Ge, S. S.
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/3/15
Y1 - 2012/3/15
N2 - This study is concerned with the synchronised tracking control for multiple agents with high-order dynamics, whereas the desired trajectory is only available for a portion of the team members. Using the weighted average of the neighbours' states as the reference signal, adaptive neural network (NN) control is designed for each agent in both full-state and output feedback cases. It is proved that the adaptive NN control law guarantees that the tracking error of each agent converges to an adjustable neighbourhood of the origin for both cases although some of them do not access the desired trajectory directly. Two simulation examples are provided to demonstrate the performance of the proposed approaches.
AB - This study is concerned with the synchronised tracking control for multiple agents with high-order dynamics, whereas the desired trajectory is only available for a portion of the team members. Using the weighted average of the neighbours' states as the reference signal, adaptive neural network (NN) control is designed for each agent in both full-state and output feedback cases. It is proved that the adaptive NN control law guarantees that the tracking error of each agent converges to an adjustable neighbourhood of the origin for both cases although some of them do not access the desired trajectory directly. Two simulation examples are provided to demonstrate the performance of the proposed approaches.
UR - http://www.scopus.com/inward/record.url?scp=84860504904&partnerID=8YFLogxK
U2 - 10.1049/iet-cta.2011.0011
DO - 10.1049/iet-cta.2011.0011
M3 - Article
AN - SCOPUS:84860504904
VL - 6
SP - 603
EP - 614
JO - IET Control Theory and Applications
JF - IET Control Theory and Applications
SN - 1751-8644
IS - 5
ER -