基于自适应差分进化的多无人机编队重构的无参考路径后退地平线控制

IF 2.5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Control Automation and Systems Pub Date : 2024-08-02 DOI:10.1007/s12555-023-0600-7
Xin Liu, Yong Chen, Siweihua Zhang, Pengcheng Fu
{"title":"基于自适应差分进化的多无人机编队重构的无参考路径后退地平线控制","authors":"Xin Liu, Yong Chen, Siweihua Zhang, Pengcheng Fu","doi":"10.1007/s12555-023-0600-7","DOIUrl":null,"url":null,"abstract":"<p>As unmanned aerial vehicles (UAVs) have limited energy resources and diverse constraints, the reconfiguration of their formation encounters substantial challenges. In this paper, we employ a leader-follower method. In order to minimize flight distance and resource consumption, a greedy algorithm is used to allocate leader and follower positions. Based on the limitations of the receding horizon control (RHC) method and the control parameterization and time discretization (CPTD) method, we propose the no reference path RHC (NRPRHC) method. The proposed method transforms the formation reconfiguration into smaller local optimization problems, leading to a reduction in the size of the optimization stages and computational complexity. For each local optimization problem, we propose the adaptive population differential evolution (APDE) algorithm to optimize the control inputs. Finally, the results are provided to illustrate the feasibility and effectiveness of the proposed method.</p>","PeriodicalId":54965,"journal":{"name":"International Journal of Control Automation and Systems","volume":"53 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"No-reference Path Receding Horizon Control for Multi-UAV Formation Reconfiguration Based on Adaptive Differential Evolution\",\"authors\":\"Xin Liu, Yong Chen, Siweihua Zhang, Pengcheng Fu\",\"doi\":\"10.1007/s12555-023-0600-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>As unmanned aerial vehicles (UAVs) have limited energy resources and diverse constraints, the reconfiguration of their formation encounters substantial challenges. In this paper, we employ a leader-follower method. In order to minimize flight distance and resource consumption, a greedy algorithm is used to allocate leader and follower positions. Based on the limitations of the receding horizon control (RHC) method and the control parameterization and time discretization (CPTD) method, we propose the no reference path RHC (NRPRHC) method. The proposed method transforms the formation reconfiguration into smaller local optimization problems, leading to a reduction in the size of the optimization stages and computational complexity. For each local optimization problem, we propose the adaptive population differential evolution (APDE) algorithm to optimize the control inputs. Finally, the results are provided to illustrate the feasibility and effectiveness of the proposed method.</p>\",\"PeriodicalId\":54965,\"journal\":{\"name\":\"International Journal of Control Automation and Systems\",\"volume\":\"53 1\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Control Automation and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s12555-023-0600-7\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Control Automation and Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12555-023-0600-7","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

由于无人驾驶飞行器(UAV)的能源资源有限,且受到多种限制,因此其编队的重新配置遇到了巨大的挑战。在本文中,我们采用了领导者-跟随者方法。为了使飞行距离和资源消耗最小化,我们采用了一种贪婪算法来分配领导者和跟随者的位置。基于后退地平线控制(RHC)方法和控制参数化与时间离散化(CPTD)方法的局限性,我们提出了无参考路径 RHC(NRPRHC)方法。该方法将编队重构转化为更小的局部优化问题,从而减少了优化阶段的规模和计算复杂度。针对每个局部优化问题,我们提出了自适应群体微分进化(APDE)算法来优化控制输入。最后,我们提供了结果来说明所提方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
No-reference Path Receding Horizon Control for Multi-UAV Formation Reconfiguration Based on Adaptive Differential Evolution

As unmanned aerial vehicles (UAVs) have limited energy resources and diverse constraints, the reconfiguration of their formation encounters substantial challenges. In this paper, we employ a leader-follower method. In order to minimize flight distance and resource consumption, a greedy algorithm is used to allocate leader and follower positions. Based on the limitations of the receding horizon control (RHC) method and the control parameterization and time discretization (CPTD) method, we propose the no reference path RHC (NRPRHC) method. The proposed method transforms the formation reconfiguration into smaller local optimization problems, leading to a reduction in the size of the optimization stages and computational complexity. For each local optimization problem, we propose the adaptive population differential evolution (APDE) algorithm to optimize the control inputs. Finally, the results are provided to illustrate the feasibility and effectiveness of the proposed method.

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
International Journal of Control Automation and Systems
International Journal of Control Automation and Systems 工程技术-自动化与控制系统
CiteScore
5.80
自引率
21.90%
发文量
343
审稿时长
8.7 months
期刊介绍: International Journal of Control, Automation and Systems is a joint publication of the Institute of Control, Robotics and Systems (ICROS) and the Korean Institute of Electrical Engineers (KIEE). The journal covers three closly-related research areas including control, automation, and systems. The technical areas include Control Theory Control Applications Robotics and Automation Intelligent and Information Systems The Journal addresses research areas focused on control, automation, and systems in electrical, mechanical, aerospace, chemical, and industrial engineering in order to create a strong synergy effect throughout the interdisciplinary research areas.
期刊最新文献
The Dynamical Model and the Slithering Controller of Continuous Snakelike Robot on Smooth Surface Adaptive Back-stepping Control of Servo Systems With Asymmetric Dead Zone Optimal Stealthy Attack With Side Information Under the Energy Constraint on Remote State Estimation Finite-time Stabilization of Fractional-order Impulsive Switched Systems With Saturated Control Input Tracking Control Design for a Bilinear Control System With Unstable and Uncertain Internal Dynamics Using Adaptive Backstepping
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1