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Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System

A consensus control law is proposed for a multi-agent system of quadrotors with leader–follower communication topology for three quadrotor agents. The genetic algorithm (GA) is the proposed optimization technique to tune the consensus control parameters. The complete nonlinear model is used without...

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Autores principales: Najm, Aws Abdulsalam, Ibraheem, Ibraheem Kasim, Azar, Ahmad Taher, Humaidi, Amjad J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349098/
https://www.ncbi.nlm.nih.gov/pubmed/32599862
http://dx.doi.org/10.3390/s20123576
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author Najm, Aws Abdulsalam
Ibraheem, Ibraheem Kasim
Azar, Ahmad Taher
Humaidi, Amjad J.
author_facet Najm, Aws Abdulsalam
Ibraheem, Ibraheem Kasim
Azar, Ahmad Taher
Humaidi, Amjad J.
author_sort Najm, Aws Abdulsalam
collection PubMed
description A consensus control law is proposed for a multi-agent system of quadrotors with leader–follower communication topology for three quadrotor agents. The genetic algorithm (GA) is the proposed optimization technique to tune the consensus control parameters. The complete nonlinear model is used without any further simplifications in the simulations, while simplification in the model is used to theoretically design the controller. Different case studies and tests are done (i.e., trajectory tracking formation and switching topology) to show the effectiveness of the proposed controller. The results show good performance in all tests while achieving the consensus of the desired formations.
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spelling pubmed-73490982020-07-22 Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System Najm, Aws Abdulsalam Ibraheem, Ibraheem Kasim Azar, Ahmad Taher Humaidi, Amjad J. Sensors (Basel) Article A consensus control law is proposed for a multi-agent system of quadrotors with leader–follower communication topology for three quadrotor agents. The genetic algorithm (GA) is the proposed optimization technique to tune the consensus control parameters. The complete nonlinear model is used without any further simplifications in the simulations, while simplification in the model is used to theoretically design the controller. Different case studies and tests are done (i.e., trajectory tracking formation and switching topology) to show the effectiveness of the proposed controller. The results show good performance in all tests while achieving the consensus of the desired formations. MDPI 2020-06-24 /pmc/articles/PMC7349098/ /pubmed/32599862 http://dx.doi.org/10.3390/s20123576 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Najm, Aws Abdulsalam
Ibraheem, Ibraheem Kasim
Azar, Ahmad Taher
Humaidi, Amjad J.
Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title_full Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title_fullStr Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title_full_unstemmed Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title_short Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System
title_sort genetic optimization-based consensus control of multi-agent 6-dof uav system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349098/
https://www.ncbi.nlm.nih.gov/pubmed/32599862
http://dx.doi.org/10.3390/s20123576
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