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通信延时环境下基于观测器的智能网联车辆队列分层协同纵向控制

朱永薪 李永福 朱浩 于树友

朱永薪, 李永福, 朱浩, 于树友. 通信延时环境下基于观测器的智能网联车辆队列分层协同纵向控制. 自动化学报, 2021, 47(x): 1−15 doi: 10.16383/j.aas.c210311
引用本文: 朱永薪, 李永福, 朱浩, 于树友. 通信延时环境下基于观测器的智能网联车辆队列分层协同纵向控制. 自动化学报, 2021, 47(x): 1−15 doi: 10.16383/j.aas.c210311
Zhu Yong-Xin, Li Yong-Fu, Zhu Hao, Yu Shu-You. Observer-based longitudinal control for connected and automated vehicles platoon subject to communication delay. Acta Automatica Sinica, 2021, 47(x): 1−15 doi: 10.16383/j.aas.c210311
Citation: Zhu Yong-Xin, Li Yong-Fu, Zhu Hao, Yu Shu-You. Observer-based longitudinal control for connected and automated vehicles platoon subject to communication delay. Acta Automatica Sinica, 2021, 47(x): 1−15 doi: 10.16383/j.aas.c210311

通信延时环境下基于观测器的智能网联车辆队列分层协同纵向控制

doi: 10.16383/j.aas.c210311
基金项目: 国家自然科学基金(U1964202, 61773082), 国家重点研发计划(2018YFB1600500)资助
详细信息
    作者简介:

    朱永薪:重庆邮电大学自动化学院硕士研究生, 主要研究方向为车辆队列控制. E-mail: zhuyongxin994@163.com

    李永福:博士, 重庆邮电大学自动化学院教授, 智能空地协同控制重庆市高校重点实验室主任. 主要研究方向为智能网联汽车和空地协同控制. 本文通信作者. E-mail: liyongfu@cqupt.edu.cn

    朱浩:博士, 重庆邮电大学自动化学院教授. 主要研究方向为智能车环境感知与信息融合. E-mail: zhuhao@cqupt.edu.cn

    于树友:博士, 吉林大学控制科学与工程系教授. 主要研究方向为模型预测控制. E-mail: shuyou@jlu.edu.cn

Observer-based Longitudinal Control for Connected and Automated Vehicles Platoon Subject to Communication Delay

Funds: Supported by National Natural Science Foundation of China (U1964202, 61773082), and National Key R&D Program of China (2018YFB1600500)
More Information
    Author Bio:

    ZHU Yong-Xin Master student at the College of Automation, Chongqing university of Posts and Telecommunications. His research interest covers platoon control of vehicles

    LI Yong-Fu Ph. D., professor at the College of Automation, Chongqing University of Posts and Telecommunica-tions. His research interest covers connected and automated vehicles and air-ground cooperative control. Corresponding author of this paper

    ZHU Hao Ph. D., professor at the College of Automation, Chongqing University of Posts and Telecommunications. His research interest covers environmental perception of intelligent vehicles and information fusion

    YU Shu-You Ph. D., professor at the Department of Control Science and Engineering, Jilin University. His research interest covers model predictive control

  • 摘要: 考虑通信延时影响的车辆队列控制问题, 本文提出了一种基于观测器的分布式车辆队列纵向控制器. 首先, 基于分层控制策略分别设计上下层控制器, 通过上层控制器优化期望加速度, 下层控制器克服车辆模型非线性实现期望加速度和实际加速度的一致, 上层控制器设计过程中, 基于三阶线性化车辆模型, 考虑观测器、车辆动态耦合特性和通信延时, 提出一种通信延时环境下基于观测器的车辆队列控制器, 利用观测器估计领导车辆加速度信息从而减轻通信负担. 然后利用Lyapunov-Krasovskii方法分析了车辆队列的稳定性, 并得出了通信延时上界, 同时利用传递函数方法分析了串稳定性. 最后通过数值仿真验证上层控制器的有效性和稳定性, 在此基础上, 利用PreScan软件中高保真车辆动态模型, 验证了所提分层控制策略的有效性.
  • 图  1  车辆队列与通信拓扑结构

    Fig.  1  Vehicle platoon and communication topology

    图  2  发动机扭矩特性逆模型

    Fig.  2  Inverse model of engine torque characteristics

    图  3  节气门/刹车控制切换策略

    Fig.  3  Switching strategy between throttle and brake controls

    图  4  基于观测器的控制器示意图

    Fig.  4  Sketch of the proposed observer-based controller

    图  5  变速器传动比

    Fig.  5  The gear ratio of transmission

    图  6  位置图: (a) 文献[12]-无延时, (b) 文献[12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) 控制器 (14) -无延时,(d) 控制器(14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    Fig.  6  Position profile: (a) controller in [12]- no time delay, (b) controller in [12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) controller (14)- no time delay, (d) controller (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    图  7  速度图: (a) 文献[12]-无延时, (b) 文献[12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) 控制器 (14) -无延时,(d) 控制器(14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    Fig.  7  Velocity profile: (a) controller in [12]- no time delay, (b) controller in [12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) controller (14)- no time delay, (d) controller (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    图  8  加速度图: (a) 文献[12]-无延时, (b) 文献[12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) 控制器 (14) -无延时,(d) 控制器(14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    Fig.  8  Acceleration profile: (a) controller in [12]- no time delay, (b) controller in [12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) controller (14)- no time delay, (d) controller (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    图  9  间距误差图: (a) 文献[12]-无延时, (b) 文献[12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) 控制器 (14) -无延时,(d) 控制器(14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    Fig.  9  Spacing error profile: (a) controller in [12]- no time delay, (b) controller in [12]-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$, (c) controller (14)- no time delay, (d) controller (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    图  10  ${z_{2,i}}(t)$${\hat z_{2,i}}(t)$: (a) 控制器 (14) -无延时, (b) 控制器 (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    Fig.  10  ${z_{2,i}}(t)$ and ${\hat z_{2,i}}(t)$: (a) controller (14)- no time delay, (b) controller (14)-$\tau (t) \in [0.1,\;0.2]{\rm{s}}$.

    图  11  基于PreScan/Simulink联合仿真平台框架示意图

    Fig.  11  Framework of the PreScan/Simulink-based Co-Simulation platform

    图  12  PreScan中的实验场景: (a) 队列初始状态, (b) 队列移动, (c) 队列停止.

    Fig.  12  Experiment scenario in PreScan: (a) Initial state of platoon, (b) Platoon move, (c) Platoon stop.

    图  13  PreScan中仿真结果: (a) 间距误差图, (b) 速度图, (c) 加速度图, (d) 节气门开度图,(e) 刹车压力图, (f). ${z_{2,i}}(t)$${\hat z_{2,i}}(t)$.

    Fig.  13  Simulation results in PreScan: (a) spacing error profile, (b) velocity profile, (c) acceleration profile, (d) throttle, (e) brake pressure, (f) ${z_{2,i}}(t)$ and ${\hat z_{2,i}}(t)$.

    表  1  控制器参数

    Table  1  Controller parameters

    参数数值单位
    $\alpha $$0.67$${{\rm{s}}^{ - 1}}$
    ${g_{o,1}}$$0.12$${{\rm{s}}^{ - 2}}$
    ${g_{o,2}}$$0.52$${{\rm{s}}^{ - 1}}$
    ${g_{o,3}}$$0.3$
    ${V_1}$$6.75$${\rm{m/s}}$
    ${V_2}$$7.91$${\rm{m/s}}$
    ${C_1}$$0.13$${{\rm{m}}^{ - 1}}$
    ${C_2}$$1.59$
    ${h_1}$$30$
    ${h_2}$$12$
    ${k_P}$$10$
    ${k_I}$$0.3$
    ${k_D}$$0.1$
    $\vartheta $$0.1$${\rm{m/}}{{\rm{s}}^2}$
    下载: 导出CSV

    表  2  PreScan中车辆模型参数

    Table  2  The parameters of vehicle model in PreScan

    参数数值单位
    $m$$1532$${\rm{kg}}$
    $g$$9.8$${\rm{m/}}{{\rm{s}}^2}$
    ${l_c}$$4.63$${\rm{m}}$
    ${C_A}$$0.31$${\rm{kg/m}}$
    ${i_0}$$2.7$
    ${\eta _{\rm{T}}}$$1$
    $f$$0.01$
    下载: 导出CSV
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  • 收稿日期:  2021-04-12
  • 修回日期:  2021-06-18
  • 网络出版日期:  2021-08-26

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