Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles

A new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers...

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Main Authors: Ming Lei, Shao-lei Zhou, Xiu-xia Yang, Gao-yang Yin
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2012/241916
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spelling doaj-770e3f76a7b74f3e942a411bf943f6442020-11-24T22:28:56ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/241916241916Complex Formation Control of Large-Scale Intelligent Autonomous VehiclesMing Lei0Shao-lei Zhou1Xiu-xia Yang2Gao-yang Yin3Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, ChinaDepartment of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, ChinaDepartment of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, ChinaDepartment of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, ChinaA new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers by exchanging information via wireless network at initial time. Then, leaders form formation geometric shape by global formation information and followers track their own virtual leaders to form line formation by local information. The formation control laws of leaders and followers are designed based on consensus algorithms. Moreover, collision-avoiding problems are considered and solved using artificial potential functions. Finally, a simulation example that consists of 25 vehicles shows the effectiveness of theory.http://dx.doi.org/10.1155/2012/241916
collection DOAJ
language English
format Article
sources DOAJ
author Ming Lei
Shao-lei Zhou
Xiu-xia Yang
Gao-yang Yin
spellingShingle Ming Lei
Shao-lei Zhou
Xiu-xia Yang
Gao-yang Yin
Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
Mathematical Problems in Engineering
author_facet Ming Lei
Shao-lei Zhou
Xiu-xia Yang
Gao-yang Yin
author_sort Ming Lei
title Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
title_short Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
title_full Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
title_fullStr Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
title_full_unstemmed Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles
title_sort complex formation control of large-scale intelligent autonomous vehicles
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2012-01-01
description A new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers by exchanging information via wireless network at initial time. Then, leaders form formation geometric shape by global formation information and followers track their own virtual leaders to form line formation by local information. The formation control laws of leaders and followers are designed based on consensus algorithms. Moreover, collision-avoiding problems are considered and solved using artificial potential functions. Finally, a simulation example that consists of 25 vehicles shows the effectiveness of theory.
url http://dx.doi.org/10.1155/2012/241916
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AT shaoleizhou complexformationcontroloflargescaleintelligentautonomousvehicles
AT xiuxiayang complexformationcontroloflargescaleintelligentautonomousvehicles
AT gaoyangyin complexformationcontroloflargescaleintelligentautonomousvehicles
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