Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots

Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots

This paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functio...

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Main Authors: Xuejing Lan, Zhenghao Wu, Wenbiao Xu, Guiyun Liu
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/8382702
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spelling doaj-ddc203cf374d414cac01c5795993a3972020-11-25T01:11:09ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/83827028382702Adaptive-Neural-Network-Based Shape Control for a Swarm of RobotsXuejing Lan0Zhenghao Wu1Wenbiao Xu2Guiyun Liu3School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaSchool of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaGuangdong Institute of Metrology, Guangzhou 510405, ChinaSchool of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaThis paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functions. Moreover, the collision avoidance, velocity consensus, and region tracking are all considered in the controller. The stability of the multirobot system has been demonstrated based on the Lyapunov theorem. Finally, three numerical simulations show the effectiveness of the proposed formation control scheme to deal with the narrow space, loss of robots, and formation merging problems.http://dx.doi.org/10.1155/2018/8382702
collection DOAJ
language English
format Article
sources DOAJ
author Xuejing Lan
Zhenghao Wu
Wenbiao Xu
Guiyun Liu
spellingShingle Xuejing Lan
Zhenghao Wu
Wenbiao Xu
Guiyun Liu
Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
Complexity
author_facet Xuejing Lan
Zhenghao Wu
Wenbiao Xu
Guiyun Liu
author_sort Xuejing Lan
title Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
title_short Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
title_full Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
title_fullStr Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
title_full_unstemmed Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots
title_sort adaptive-neural-network-based shape control for a swarm of robots
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2018-01-01
description This paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functions. Moreover, the collision avoidance, velocity consensus, and region tracking are all considered in the controller. The stability of the multirobot system has been demonstrated based on the Lyapunov theorem. Finally, three numerical simulations show the effectiveness of the proposed formation control scheme to deal with the narrow space, loss of robots, and formation merging problems.
url http://dx.doi.org/10.1155/2018/8382702
work_keys_str_mv AT xuejinglan adaptiveneuralnetworkbasedshapecontrolforaswarmofrobots
AT zhenghaowu adaptiveneuralnetworkbasedshapecontrolforaswarmofrobots
AT wenbiaoxu adaptiveneuralnetworkbasedshapecontrolforaswarmofrobots
AT guiyunliu adaptiveneuralnetworkbasedshapecontrolforaswarmofrobots
_version_ 1725172727640227840

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