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

被引：4
|
作者：
Lan, Xuejing [1 ,2 ]
Wu, Zhenghao [1 ]
Xu, Wenbiao [3 ]
Liu, Guiyun [1 ,4 ]
机构：
[1] Guangzhou Univ, Sch Mech & Elect Engn, Guangzhou 510006, Guangdong, Peoples R China
[2] MOE Key Lab Image Proc & Intelligence Control, Wuhan 430074, Hubei, Peoples R China
[3] Guangdong Inst Metrol, Guangzhou 510405, Guangdong, Peoples R China
[4] Ctr Intelligent Equipment & Internet Connected Sy, Guangzhou, Guangdong, Peoples R China
来源：
COMPLEXITY | 2018年
基金：
中国国家自然科学基金;
关键词：
FORMATION STABILIZATION;
D O I：
10.1155/2018/8382702
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
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.
引用
收藏
页数：8
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