双端通信时延下网联车辆纵向队列的分布式控制器设计与分析

doi:10.3969/j.issn.1674-8484.2024.03.014

汽车安全与节能学报 ›› 2024, Vol. 15 ›› Issue (3): 402-412.DOI: 10.3969/j.issn.1674-8484.2024.03.014

双端通信时延下网联车辆纵向队列的分布式控制器设计与分析

王靖瑶¹^,²(), 黄江山¹, 郭景华¹^,², 李克强²

1.厦门大学航空航天学院，厦门361005，中国
2.清华大学，智能绿色车辆与交通全国重点实验室（原汽车安全与节能国家重点实验室），北京 100084，中国

收稿日期:2023-10-31 修回日期:2023-12-21 出版日期:2024-06-30 发布日期:2024-07-01
作者简介:王靖瑶（1988—），女（汉），河北，副教授。E-mail：wangjingyao1@xmu.edu.cn。
基金资助:
汽车安全与节能国家重点实验室开放基金资助项目(KFY2206)

Design and analysis of distributed controller for longitudinal platoon of networked vehicles under the bidirectional communication delay

WANG Jingyao¹^,²(), HUANG Jiangshan¹, GUO Jinghua¹^,², LI Keqiang²

1. School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
2. State Key Laboratory of Intelligent Green Vehicle and Mobility (Former: State Key Laboratory of Automotive Safety and Energy), Tsinghua University, Beijing 100084, China

Received:2023-10-31 Revised:2023-12-21 Online:2024-06-30 Published:2024-07-01

摘要/Abstract

摘要：

网联车辆队列系统的双端通信时延会极大影响队列的控制性能，而且在极端情况下，甚至可能引发队列失稳、发生碰撞的现象。该文在充分考虑车云双端通信时延的基础上，提出了一种基于云的分布式控制算法。通过一定假设，对云控场景下的车辆队列使用采样控制系统的方法进行建模，将双端通信时延进行统一；使用Riccati不等式设计了状态反馈分布式控制器，使用Lyapunov-Razumikin定理分析了控制算法的渐近稳定性，进而得到时变时延上界与通信拓扑、耦合增益之间的关系。结果表明：存在一个合适的耦合增益使得所能容忍的时延上界最大，且通信拓扑Laplacian矩阵最大与最小特征值的比值与时延上界大小呈负相关的趋势。

关键词: 云控制系统, 网联车辆队列, 时变时延, 双端通信时延

Abstract:

The bidirectional communication delay in connected vehicle platoon systems can significantly impact the control performance of the platoon. In extreme cases, it may even result in instability or collisions. A cloud-based distributed control algorithm was proposed, fully considering the bidirectional communication delay between vehicles and the cloud. Under certain assumptions, the vehicle platoon under cloud control was modeled with sampled control system methods, leading to the unification of bidirectional communication delay. A state feedback distributed controller was designed using the Riccati inequality, and the Lyapunov-Razumikhin theorem was utilized to analyze the asymptotic stability of the control algorithm, establishing the relationship between the upper bound of time-varying delay and the communication topology and coupling gain. The results show that the existence of an optimal coupling gain maximizes the tolerated upper bound of delay, and the ratio of the maximum to minimum eigenvalues of the Laplacian matrix of the communication topology is negatively correlated with the upper bound.

Key words: cloud control system, vehicle platoon, time-varying delay, bidirectional communication delay

中图分类号:

U461.8

王靖瑶, 黄江山, 郭景华, 李克强. 双端通信时延下网联车辆纵向队列的分布式控制器设计与分析[J]. 汽车安全与节能学报, 2024, 15(3): 402-412.

WANG Jingyao, HUANG Jiangshan, GUO Jinghua, LI Keqiang. Design and analysis of distributed controller for longitudinal platoon of networked vehicles under the bidirectional communication delay[J]. Journal of Automotive Safety and Energy, 2024, 15(3): 402-412.

图/表 8

图1 双端通信时延下网联车辆队列系统

图2 输入时延系统转换方法

图3 车辆队列中常见的通信拓扑结构

图4 耦合增益c与时延上界关系

通信拓扑	Laplacian矩阵最大最小特征值之比	时延上界 10^-5 s
前车跟随式 (PF)	1	915
领航-前车跟随式 (PLF)	2	229
双前车跟随式 (TPF)	2	229
双领航-前车跟随式 (TPLF)	3	101
双向前车跟随式 (BDL)	4.7321	40
双向跟随式 (BD)	64.8855	0.217

表1 不同通信拓扑的时延上界

图5 不同Riccati不等式参数下的时延上界

图6 不同发动机时滞常数倒数下的时延上界

图7 控制协议的距离误差曲线、速度误差曲线以及加速度曲线

参考文献 16

[1]	XIA Yuanqing. From networked control systems to cloud control systems[C]// Proceed 31st Chin Contr Conf. IEEE, 2012: 5878-5883.
[2]	国家发展改革委, 中央网信办, 科技部, 等. 关于印发《智能汽车创新发展战略》的通知[J]. 科学中国人, 2020(9): 62-65.
	National Development and Reform Commission, Cyberspace Administration of China,Ministry of Science and Technology, et al. Notice on Printing and Distributing the Innovation and Development Strategy for Smart Vehicles[J]. Scientific Chinese, 2020(9): 62-65. (in Chinese)
[3]	李克强, 常雪阳, 李家文, 等. 智能网联汽车云控系统及其实现[J]. 汽车工程, 2020, 42(12): 1595-1605. doi: 10.19562/j.chinasae.qcgc.2020.12.001
	LI Keqiang, CHANG Xueyang, LI Jiawen, et al. Cloud control system for intelligent and connected vehicles and its application[J]. Autom Engineering, 2020, 42(12): 1595-1605. (in Chinese)
[4]	Shengbo Eben Li, ZHENG Yang, LI Keqiang, et al. An overview of vehicular platoon control under the four-component framework[C]// 2015 IEEE Intel Vehi Symp (IV). IEEE, 2015: 286-291.
[5]	郭景华, 李克强, 罗禹贡. 智能车辆运动控制研究综述[J]. 汽车安全与节能学报, 2016, 7(2): 151-159.
	GUO Jinghua, LI Keqiang, LUO Yugong. Review on the research of motion control for intelligent vehicles[J]. J Autom Safe Energ, 2016, 7(2): 151-159. (in Chinese)
[6]	许庆, 潘济安, 李克强, 等. 不可靠通信的云控场景下网联车辆控制器的设计[J]. 汽车工程, 2021, 43(4): 527-536.
	XU Qing, PAN Ji’an, LI Keqiang, et al. Design of connected vehicle controller under cloud control scenes with unreliable communication[J]. Autom Engineering, 2021, 43(4): 527-536. (in Chinese)
[7]	LI Shuyan, LI Ruili, GAO bolin, et al. Predictive adaptive cruise control for heavy-duty vehicle based on cloud control system[C]// 2022 IEEE 25th Int’l Conf Intel Transport Syst (ITSC). IEEE, 2022: 2998-3003.
[8]	Montanaro U, Fallah S, Dianati M, et al. On a fully self-organizing vehicle platooning supported by cloud computing[C]// 2018 5th Int’l Conf Inte Things: Syst, Manag Secur. IEEE, 2018: 295-302.
[9]	赵菲, 王建, 张天雷, 等. 云控场景下车辆队列的模型预测控制方法[J]. 汽车工程, 2022, 44(2): 179-189.
	ZHAO Fei, WANG Jian, ZHANG Tianlei, et al. Model predictive control method for vehicle platoon under cloud control scenes[J]. Autom Engineering, 2022, 44(2): 179-189. (in Chinese)
[10]	Quadri C, Mancuso V, Marsan M A, et al. Edge-based platoon control[J]. Comput Commun, 2022, 181: 17-31.
[11]	Bernardo M D, Salvi A, Santini S. Distributed consensus strategy for platooning of vehicles in the presence of time-varying heterogeneous communication delays[J]. IEEE Trans Intel Transport Syst, 2014, 16(1): 102-112.
[12]	Fiengo G, Lui D G, Petrillo A, et al. Distributed robust PID control for leader tracking in uncertain connected ground vehicles with V2V communication delay[J]. IEEE/ASME Trans Mechatron, 2019, 24(3): 1153-1165.
[13]	HUANG Darong, LI Shaoqian, ZHANG Zhenyuan, et al. Design and analysis of longitudinal controller for the platoon with time-varying delay[J]. IEEE Trans Intel Transport Syst, 2022, 23(12): 23628-23639.
[14]	ZHENG Yang, LI Shengbo, WANG Jianqiang, et al. Stability and scalability of homogeneous vehicular platoon: Study on the influence of information flow topologies[J]. IEEE Trans Intel Transport Syst, 2015, 17(1): 14-26.
[15]	XIE Lihua, de Souza C E. Robust H/sub infinity/control for linear systems with norm-bounded time-varying uncertainty[C]// 29th IEEE Conf Deci Contr. IEEE, 1990, 2: 1034-1035.
[16]	Hale J K, Lunel S M V. Introduction to Functional Differential Equations[M]. Springer Science & Business Media, Berlin, 2013: 151-152.

双端通信时延下网联车辆纵向队列的分布式控制器设计与分析

Design and analysis of distributed controller for longitudinal platoon of networked vehicles under the bidirectional communication delay

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 16

相关文章 9

编辑推荐

Metrics

本文评价

期刊信息

在线期刊

作者中心

审稿中心

联系我们

[1]	尹燕莉, 王福振, 詹森, 黄学江, 张鑫新, 张富椿. 基于KL散度工况识别的混合动力汽车队列的分层控制[J]. 汽车安全与节能学报, 2024, 15(2): 242-252.
[2]	王宙, 褚端峰, 高博麟, 梅润, 钟薇. 云支持的分层式车辆队列预测性巡航控制[J]. 汽车安全与节能学报, 2023, 14(5): 591-599.
[3]	罗闯, 许亮. 基于ISSA的燃料电池多电源模糊能量管理策略[J]. 汽车安全与节能学报, 2023, 14(4): 496-504.
[4]	修国涛, 谢辉, 宋康, 毕凤荣. 基于驾驶员经验的无人驾驶车辆平行泊车操作模型[J]. 汽车安全与节能学报, 2023, 14(2): 191-201.
[5]	吴浩, 丁文敏, 魏广杰, 胡均, 游道亮. 基于路况和驾驶习惯的自适应能量回收控制策略[J]. 汽车安全与节能学报, 2023, 14(1): 106-117.
[6]	付雪青, 王宝森, 杨建军, 高海洋, 何邦全, 赵华, 郭文翠, 刘双喜. 基于双状态动态规划混动汽车坡道生态驾驶策略[J]. 汽车安全与节能学报, 2021, 12(3): 373-379.
[7]	刘建辉, 姚方方, 张彦. 混合动力汽车参数的交叉—变异蜂群算法优化[J]. 汽车安全与节能学报, 2021, 12(2): 186-192.
[8]	董振鹏, 祖炳锋, 周建伟, 徐佳晨. 基于交通信息的电动汽车制动策略及仿真[J]. 汽车安全与节能学报, 2021, 12(1): 35-42.
[9]	牛亚卓, 聂国乐, 杨建军, 刘双喜, 白巴特尔. 基于多工况分析的插电式混合动力汽车节能控制策略[J]. 汽车安全与节能学报, 2020, 11(4): 546-552.