Multi-pursuer single-evader privacy-preserving differential games

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED
Yinglu Zhou, Yinya Li, Andong Sheng, Guoqing Qi
{"title":"Multi-pursuer single-evader privacy-preserving differential games","authors":"Yinglu Zhou,&nbsp;Yinya Li,&nbsp;Andong Sheng,&nbsp;Guoqing Qi","doi":"10.1016/j.amc.2025.129612","DOIUrl":null,"url":null,"abstract":"<div><div>This paper investigates a multi-pursuer single-evader (MPSE) differential game with privacy-preserving over time-varying unbalanced directed network topologies. A novel player decomposition mechanism for the MPSE differential game with privacy-preserving is proposed. Distributed control strategies under this mechanism are then designed based on the Hamilton–Jacobi–Isaacs (HJI) and the Nash equilibrium of these strategies is proved. The interception condition related to a proposed novel coupling gain and reconstructed symmetric Laplacian matrix based on the weight balancing method is derived to guarantee that multiple pursuers successfully intercept the evader over time-varying unbalanced directed network topologies. Privacy-preserving is also verified to ensure that the state of any pursuer is not disclosed. Especially, the privacy-preserving algorithm is proved to be applicable to the continuous-time system, which is different from most existing studies whose research system is the discrete-time case. Illustrative examples are given to demonstrate that all pursuers can intercept the evader and that the private information they carry can be preserved.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"508 ","pages":"Article 129612"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325003388","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

This paper investigates a multi-pursuer single-evader (MPSE) differential game with privacy-preserving over time-varying unbalanced directed network topologies. A novel player decomposition mechanism for the MPSE differential game with privacy-preserving is proposed. Distributed control strategies under this mechanism are then designed based on the Hamilton–Jacobi–Isaacs (HJI) and the Nash equilibrium of these strategies is proved. The interception condition related to a proposed novel coupling gain and reconstructed symmetric Laplacian matrix based on the weight balancing method is derived to guarantee that multiple pursuers successfully intercept the evader over time-varying unbalanced directed network topologies. Privacy-preserving is also verified to ensure that the state of any pursuer is not disclosed. Especially, the privacy-preserving algorithm is proved to be applicable to the continuous-time system, which is different from most existing studies whose research system is the discrete-time case. Illustrative examples are given to demonstrate that all pursuers can intercept the evader and that the private information they carry can be preserved.
多追求者单逃避者隐私保护差分博弈
研究时变非平衡有向网络拓扑下具有隐私保护的多追踪者单逃避者微分对策。针对具有隐私保护的MPSE微分对策,提出了一种新的参与人分解机制。然后基于Hamilton-Jacobi-Isaacs (HJI)设计了该机制下的分布式控制策略,并证明了这些策略的纳什均衡。为了保证在时变非平衡有向网络拓扑中多个追踪者能够成功拦截逃避者,提出了一种基于权重平衡方法的新型耦合增益和重构对称拉普拉斯矩阵的拦截条件。还验证了隐私保护,以确保不会泄露任何追踪者的状态。特别是,证明了该隐私保护算法适用于连续时间系统,这不同于大多数现有研究的研究系统是离散时间情况。举例说明,所有追踪者都可以拦截逃避者,并且他们携带的私人信息可以被保留。
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
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
×
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