Distributed Adaptive NN Resilient Optimal Control for Heterogeneous Vehicular Platoon Systems Under DoS Attacks

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-09 DOI:10.1109/TNSE.2025.3559130

Zixin Tian;Yongming Li;Shaocheng Tong

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引用次数: 0

Abstract

Vehicular platoon systems are multiple intelligent vehicles travelling longitudinally and maintaining a desired inter-vehicle spacing. In this paper, a distributed adaptive neural network (NN) resilient optimal control problem is investigated for heterogeneous vehicular platoon systems (VPSs) subject to denial-of-service (DoS) attacks. Since the communication channels are suffered from DoS attacks, the leader's information cannot be continuously obtained by the heterogeneous VPSs, a distributed resilient filter is utilized to estimate unknown leader. Based on the designed distributed resilient filter and the differential graphical game strategy, a distributed adaptive NN resilient optimal control scheme is formulated through a sliding mode surface. The developed resilient optimal control scheme can ensure the following vehicles can asymptotically track the leader, and obtain the global Nash equilibrium solution of the differential graphical game strategy. Finally, the validity of the proposed resilient optimal control scheme is demonstrated by simulation.

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DoS攻击下异构车辆排系统的分布式自适应神经网络弹性最优控制

车辆排系统是多辆智能车辆纵向行驶并保持所需的车辆间距。研究了异构车辆排系统（vps）在拒绝服务攻击下的分布式自适应神经网络弹性最优控制问题。针对通信通道遭受DoS攻击，异构vps无法连续获取领导者信息的问题，采用分布式弹性滤波器估计未知领导者。基于所设计的分布式弹性滤波器和微分图形博弈策略，通过滑模面构造了分布式自适应神经网络弹性最优控制方案。所提出的弹性最优控制方案能保证后续车辆能渐近跟踪领头车辆，并得到微分图形对策的全局纳什均衡解。最后，通过仿真验证了所提弹性最优控制方案的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.