具有网络不完善的多无人机系统基于博弈论的生物启发分布式智能群集控制

Mohammad Jafari, Hao Xu
{"title":"具有网络不完善的多无人机系统基于博弈论的生物启发分布式智能群集控制","authors":"Mohammad Jafari, Hao Xu","doi":"10.1109/SSCI.2018.8628814","DOIUrl":null,"url":null,"abstract":"In this paper, a game theoretic based biologically-inspired distributed intelligent control methodology is proposed to overcome challenges in networked multi-UAV, i.e., networked imperfections and uncertainty from environment and system. Considering the limited computational ability in the practical onboard micro-controller, the proposed method is adopted based on the game theory, and the emotional learning phenomenon in the mammalian limbic system. The learning capability and low computational complexity of the proposed technique makes it a propitious tool for implementing in networked multi-UAV flocking even in presence of the network imperfections and uncertainty from environment and system. Lyapunov analysis and computer-aid numerical simulation results of the implementation of the proposed methodology demonstrate the effectiveness of this algorithm.","PeriodicalId":235735,"journal":{"name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Game Theoretic Based Biologically-Inspired Distributed Intelligent Flocking Control for Multi-UAV Systems with Network Imperfections\",\"authors\":\"Mohammad Jafari, Hao Xu\",\"doi\":\"10.1109/SSCI.2018.8628814\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a game theoretic based biologically-inspired distributed intelligent control methodology is proposed to overcome challenges in networked multi-UAV, i.e., networked imperfections and uncertainty from environment and system. Considering the limited computational ability in the practical onboard micro-controller, the proposed method is adopted based on the game theory, and the emotional learning phenomenon in the mammalian limbic system. The learning capability and low computational complexity of the proposed technique makes it a propitious tool for implementing in networked multi-UAV flocking even in presence of the network imperfections and uncertainty from environment and system. Lyapunov analysis and computer-aid numerical simulation results of the implementation of the proposed methodology demonstrate the effectiveness of this algorithm.\",\"PeriodicalId\":235735,\"journal\":{\"name\":\"2018 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI.2018.8628814\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI.2018.8628814","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

本文提出了一种基于博弈论的生物启发分布式智能控制方法,以克服网络化多无人机存在的网络不完善和环境、系统不确定性等问题。考虑到实际板载微控制器的计算能力有限,本文提出的方法是基于博弈论和哺乳动物边缘系统的情绪学习现象。该方法具有较强的学习能力和较低的计算复杂度,可以在存在网络不完善和环境、系统不确定性的情况下实现网络化多无人机集群。李雅普诺夫分析和计算机辅助数值模拟结果验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Game Theoretic Based Biologically-Inspired Distributed Intelligent Flocking Control for Multi-UAV Systems with Network Imperfections
In this paper, a game theoretic based biologically-inspired distributed intelligent control methodology is proposed to overcome challenges in networked multi-UAV, i.e., networked imperfections and uncertainty from environment and system. Considering the limited computational ability in the practical onboard micro-controller, the proposed method is adopted based on the game theory, and the emotional learning phenomenon in the mammalian limbic system. The learning capability and low computational complexity of the proposed technique makes it a propitious tool for implementing in networked multi-UAV flocking even in presence of the network imperfections and uncertainty from environment and system. Lyapunov analysis and computer-aid numerical simulation results of the implementation of the proposed methodology demonstrate the effectiveness of this algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信