Distributed adaptive iterative learning control for 2D multi agent systems

Abstract This letter addresses the output consensus problem for a class of two‐dimensional (2D) multi agent systems (MASs) described by Fornasini–Marchesini model. By transforming the 2D agent into a compact form, an adaptive variable, which adjusted by the tracking errors of itself and the neighbou...

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Main Authors: Qingyuan Xu, Qingquan Mai, Boxian Wang, Kai Wan, Yunshan Wei
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Electronics Letters
Subjects:
Online Access:https://doi.org/10.1049/ell2.13263
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author Qingyuan Xu
Qingquan Mai
Boxian Wang
Kai Wan
Yunshan Wei
author_facet Qingyuan Xu
Qingquan Mai
Boxian Wang
Kai Wan
Yunshan Wei
author_sort Qingyuan Xu
collection DOAJ
description Abstract This letter addresses the output consensus problem for a class of two‐dimensional (2D) multi agent systems (MASs) described by Fornasini–Marchesini model. By transforming the 2D agent into a compact form, an adaptive variable, which adjusted by the tracking errors of itself and the neighbour agents, is designed to approximate the unknown varying coefficient. Then, based on the approximated coefficient and the iteration‐varying reference surfaces, the distributed adaptive iterative learning control strategy is obtained. The output consensus of the 2D multi agent is proved. Simulations are included to verify the effectiveness of the investigated distributed adaptive ILC for 2D MASs with random variations on initial condition and reference surface.
format Article
id doaj-art-3a9682ef2c954c3bb7c7c0ceeb99973f
institution DOAJ
issn 0013-5194
1350-911X
language English
publishDate 2024-07-01
publisher Wiley
record_format Article
series Electronics Letters
spelling doaj-art-3a9682ef2c954c3bb7c7c0ceeb99973f2025-08-20T02:45:41ZengWileyElectronics Letters0013-51941350-911X2024-07-016013n/an/a10.1049/ell2.13263Distributed adaptive iterative learning control for 2D multi agent systemsQingyuan Xu0Qingquan Mai1Boxian Wang2Kai Wan3Yunshan Wei4School of Electronic and Information Guangdong Polytechnic Normal University Guangzhou Guangdong ChinaSchool of Electronic and Information Guangdong Polytechnic Normal University Guangzhou Guangdong ChinaSchool of Electronic and Information Guangdong Polytechnic Normal University Guangzhou Guangdong ChinaSchool of Electronic Information and Electrical Engineering Huizhou University Huizhou Guangdong ChinaSchool of Electronics and Communication Engineering Guangzhou University Guangzhou ChinaAbstract This letter addresses the output consensus problem for a class of two‐dimensional (2D) multi agent systems (MASs) described by Fornasini–Marchesini model. By transforming the 2D agent into a compact form, an adaptive variable, which adjusted by the tracking errors of itself and the neighbour agents, is designed to approximate the unknown varying coefficient. Then, based on the approximated coefficient and the iteration‐varying reference surfaces, the distributed adaptive iterative learning control strategy is obtained. The output consensus of the 2D multi agent is proved. Simulations are included to verify the effectiveness of the investigated distributed adaptive ILC for 2D MASs with random variations on initial condition and reference surface.https://doi.org/10.1049/ell2.13263adaptive controllearning systems
spellingShingle Qingyuan Xu
Qingquan Mai
Boxian Wang
Kai Wan
Yunshan Wei
Distributed adaptive iterative learning control for 2D multi agent systems
Electronics Letters
adaptive control
learning systems
title Distributed adaptive iterative learning control for 2D multi agent systems
title_full Distributed adaptive iterative learning control for 2D multi agent systems
title_fullStr Distributed adaptive iterative learning control for 2D multi agent systems
title_full_unstemmed Distributed adaptive iterative learning control for 2D multi agent systems
title_short Distributed adaptive iterative learning control for 2D multi agent systems
title_sort distributed adaptive iterative learning control for 2d multi agent systems
topic adaptive control
learning systems
url https://doi.org/10.1049/ell2.13263
work_keys_str_mv AT qingyuanxu distributedadaptiveiterativelearningcontrolfor2dmultiagentsystems
AT qingquanmai distributedadaptiveiterativelearningcontrolfor2dmultiagentsystems
AT boxianwang distributedadaptiveiterativelearningcontrolfor2dmultiagentsystems
AT kaiwan distributedadaptiveiterativelearningcontrolfor2dmultiagentsystems
AT yunshanwei distributedadaptiveiterativelearningcontrolfor2dmultiagentsystems