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高速动车组强耦合模型的分布式滑模控制策略

李中奇 金柏 杨辉 谭畅 付雅婷

李中奇, 金柏, 杨辉, 谭畅, 付雅婷. 高速动车组强耦合模型的分布式滑模控制策略. 自动化学报, 2020, 46(3): 495−508 doi: 10.16383/j.aas.190216
引用本文: 李中奇, 金柏, 杨辉, 谭畅, 付雅婷. 高速动车组强耦合模型的分布式滑模控制策略. 自动化学报, 2020, 46(3): 495−508 doi: 10.16383/j.aas.190216
Li Zhong-Qi, Jin Bai, Yang Hui, Tan Chang, Fu Ya-Ting. Distributed sliding mode control strategy for high-speed EMU strong coupling model. Acta Automatica Sinica, 2020, 46(3): 495−508 doi: 10.16383/j.aas.190216
Citation: Li Zhong-Qi, Jin Bai, Yang Hui, Tan Chang, Fu Ya-Ting. Distributed sliding mode control strategy for high-speed EMU strong coupling model. Acta Automatica Sinica, 2020, 46(3): 495−508 doi: 10.16383/j.aas.190216

高速动车组强耦合模型的分布式滑模控制策略

doi: 10.16383/j.aas.190216
基金项目: 国家自然科学基金(51565012, 61673172, 61663013, 61803155)资助
详细信息
    作者简介:

    李中奇:华东交通大学电气与自动化工程学院教授, 工学博士. 主要研究方向为列车运行过程建模与控制. 本文通信作者. E-mail: lzq0828@163.com

    金柏:华东交通大学电气与自动化工程学院硕士研究生. 主要研究方向为列车运行过程建模与控制. E-mail: jinbai0009@163.com

    杨辉:华东交通大学电气与自动化工程学院教授, 工学博士. 主要研究方向为复杂系统建模, 控制与运行优化. E-mail: yhshuo@263.net

    谭畅:华东交通大学电气与自动化工程学院副教授, 工学博士. 主要研究方向为复杂系统建模, 控制与运行优化. E-mail: lovetanchang@163.com

    付雅婷:华东交通大学电气与自动化工程学院讲师, 工学博士. 主要研究方向为轨道交通自动化和运行优化. E-mail: fuyating0103@163.com

Distributed Sliding Mode Control Strategy for High-speed EMU Strong Coupling Model

Funds: Supported by National Natural Science Foundation of China (51565012, 61673172, 61663013, 61803155)
  • 摘要: 高速动车组是由多节车辆与钩缓装置链接而成的复杂系统. 将钩缓装置等效成弹簧 − 阻尼器系统, 分析动车组运行过程中钩缓装置对相邻车辆作用的动力学机理, 明确作用方式, 建立高速动车组的强耦合模型. 根据列车模型动力或制动力输入的分散特征, 设计分布式神经网络滑模控制策略, 对高速动车组进行速度跟踪控制. 为减小速度跟踪过程中未知因素对高速动车组控制精度的影响, 利用列车历史运行数据, 采用历史工况数据中心对当前控制律输出进行补偿以提高控制精度与实用稳定性. 采用高速动车组运行仿真平台的仿真实验结果表明, 该建模方法较以往多质点模型更能体现高速动车组运行特性, 且采用补偿规则的控制策略优于传统控制效果.
  • 图  1  国内某型号的高速动车组

    Fig.  1  A certain type of high-speed EMU in China

    图  2  高速动车组弹簧−阻尼器系统强耦合模型

    Fig.  2  Strong coupling model of spring damper system for high speed EMU

    图  3  高速动车组动车与拖车链接示意图

    Fig.  3  Schematic diagram of high-speed EMU locomotive and trailer link

    图  4  动车与拖车系统动力学分析

    Fig.  4  Dynamic analysis of locomotive and trailer system

    图  5  高速动车组动车与动车链接示意图

    Fig.  5  Schematic diagram of high-speed EMU locomotive and locomotive link

    图  6  动车 − 动车系统动力学分析

    Fig.  6  Locomotive-locomotive system dynamics analysis

    7  两种延时类型的作用方式

    7  Two types of delay mode

    图  8  高速动车组分布式神经网络自适应滑模控制框图

    Fig.  8  Block diagram of neural network adaptive sliding mode control for high speed EMUs

    图  9  优化控制器输出的补偿规则逻辑

    Fig.  9  Optimize the compensation rule logic of the controller output

    图  10  工况数据中心修正算法框图

    Fig.  10  Data center correction algorithm block diagram

    图  11  高速动车组虚拟自动驾驶平台

    Fig.  11  Virtual automatic driving platform for high speed EMUs

    图  12  各车辆速度跟踪效果

    Fig.  12  Vehicles speed tracking effect

    图  13  1车辆速度跟踪误差

    Fig.  13  The speed tracking error of the first vehicle

    图  14  1车辆和2车辆间车钩力变化

    Fig.  14  The change in the hook force between the first and second vehicle

    图  15  2车辆控制力变化

    Fig.  15  The control force change of the second vehicle

    图  16  本文补偿规则下的数据修正曲线

    Fig.  16  Data correction curve under compensation rule

    表  1  CRH380A型动车组各节车辆质量

    Table  1  The CRH380A EMU vehicle quality

    车辆类型质量 (kg)
    1拖车60 800
    2动车62 000
    3动车60 800
    4动车56 560
    5动车55 800
    6动车60 800
    7动车62 000
    8拖车60 800
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-03-21
  • 录用日期:  2019-07-30
  • 网络出版日期:  2020-03-30
  • 刊出日期:  2020-03-30

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