DoS 攻击下基于事件触发的异构互联车辆排分布式模型预测控制

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
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引用次数: 0

摘要

本文关注拒绝服务(DoS)攻击下异构互联车辆排(CVP)的分布式模型预测控制(DMPC)。首先,本文提出了一种基于车辆间信息交互的动态事件触发机制(DETM),以减轻通信和计算负担。由于每辆车的触发时刻无法同步,且 DoS 攻击会破坏车辆间的通信,因此设计了一种数据包补充机制,以确保信息交互的完整性和有效性。然后,通过在 DMPC 算法中添加鲁棒性约束来处理外部干扰的影响。此外,还证明了 DMPC 算法的递归可行性和 CVP 控制系统的输入-状态实际稳定性(ISPS)。最后,通过仿真和对比结果验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic event-triggering-based distributed model predictive control of heterogeneous connected vehicle platoon under DoS attacks

This paper is concerned with the distributed model predictive control (DMPC) for heterogeneous connected vehicle platoon (CVP) under denial-of-service (DoS) attacks. Firstly, a dynamic event-triggering mechanism (DETM) based on the information interaction between vehicles is proposed to reduce the communication and computational burdens. Due to the fact that the triggering moment for each vehicle cannot be synchronized and DoS attacks can break the communication between vehicles, a packet replenishment mechanism is designed to ensure the integrity and effectiveness of information interaction. Then, the effect of external disturbance is handled by adding robustness constraints to the DMPC algorithm. In addition, the recursive feasibility of the DMPC algorithm and input-to-state practical stability (ISPS) of the CVP control system are demonstrated. Finally, the effectiveness of the algorithm is verified by simulation and comparison results.

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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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