Fault-Tolerant Adaptive Neural Control of Multi-UAVs Against Actuator Faults

Ziquan Yu, You-min Zhang, Y. Qu, C. Su, Yintao Zhang, Zhewen Xing
{"title":"Fault-Tolerant Adaptive Neural Control of Multi-UAVs Against Actuator Faults","authors":"Ziquan Yu, You-min Zhang, Y. Qu, C. Su, Yintao Zhang, Zhewen Xing","doi":"10.1109/ICUAS.2019.8798328","DOIUrl":null,"url":null,"abstract":"This paper is concerned with the fault-tolerant cooperative control (FTCC) problem of multiple unmanned aerial vehicles (multi-UAVs) in the communication network. By exploiting neural network (NN) to approximate the nonlinear terms existing in the highly nonlinear multi-UAVs system, a distributed neural adaptive control scheme is proposed when only a subset of follower UAVs has access to the leader UAV’s states. To solve the problem of “explosion of complexity” in traditional backstepping architecture and reduce the number of online updating parameters of NN, dynamic surface control (DSC) and minimal learning parameter techniques are employed to reduce the computational complexity. Furthermore, by combining graph theory and Lyapunov approach, it is proved that velocities and altitudes of all follower UAVs can track the velocity and altitude of the leader UAV. Finally, simulation results are presented to verify the effectiveness of the proposed control scheme.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS.2019.8798328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

This paper is concerned with the fault-tolerant cooperative control (FTCC) problem of multiple unmanned aerial vehicles (multi-UAVs) in the communication network. By exploiting neural network (NN) to approximate the nonlinear terms existing in the highly nonlinear multi-UAVs system, a distributed neural adaptive control scheme is proposed when only a subset of follower UAVs has access to the leader UAV’s states. To solve the problem of “explosion of complexity” in traditional backstepping architecture and reduce the number of online updating parameters of NN, dynamic surface control (DSC) and minimal learning parameter techniques are employed to reduce the computational complexity. Furthermore, by combining graph theory and Lyapunov approach, it is proved that velocities and altitudes of all follower UAVs can track the velocity and altitude of the leader UAV. Finally, simulation results are presented to verify the effectiveness of the proposed control scheme.
针对执行器故障的多无人机容错自适应神经控制
本文研究了通信网络中多架无人机的容错协同控制(FTCC)问题。通过利用神经网络对高度非线性多无人机系统中存在的非线性项进行近似,提出了一种只有一部分跟随无人机能够访问领航无人机状态的分布式神经自适应控制方案。为了解决传统反演结构中“复杂度爆炸”的问题,减少神经网络在线更新参数的次数,采用动态面控制(DSC)和最小学习参数技术来降低计算复杂度。进一步,结合图论和李亚普诺夫方法,证明了所有跟随无人机的速度和高度能够跟踪领头无人机的速度和高度。最后给出了仿真结果,验证了所提控制方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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