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带时变计算时间和计算误差的倒立摆视觉H控制研究

杜大军 占国华 李汪佩 费敏锐 周文举

杜大军, 占国华, 李汪佩, 费敏锐, 周文举. 带时变计算时间和计算误差的倒立摆视觉H∞控制研究. 自动化学报, 2019, 45(2): 334-348. doi: 10.16383/j.aas.2018.c170393
引用本文: 杜大军, 占国华, 李汪佩, 费敏锐, 周文举. 带时变计算时间和计算误差的倒立摆视觉H控制研究. 自动化学报, 2019, 45(2): 334-348. doi: 10.16383/j.aas.2018.c170393
DU Da-Jun, ZHAN Guo-Hua, LI Wang-Pei, FEI Min-Rui, ZHOU Wen-Ju. Research of Visual H∞ Control of Inverted Pendulum With Time-varying Computational Time and Computational Error. ACTA AUTOMATICA SINICA, 2019, 45(2): 334-348. doi: 10.16383/j.aas.2018.c170393
Citation: DU Da-Jun, ZHAN Guo-Hua, LI Wang-Pei, FEI Min-Rui, ZHOU Wen-Ju. Research of Visual H Control of Inverted Pendulum With Time-varying Computational Time and Computational Error. ACTA AUTOMATICA SINICA, 2019, 45(2): 334-348. doi: 10.16383/j.aas.2018.c170393

带时变计算时间和计算误差的倒立摆视觉H控制研究

doi: 10.16383/j.aas.2018.c170393
基金项目: 

国家自然科学基金 61633016

国家自然科学基金 61773253

国家自然科学基金 61473182

上海市科学技术委员会 15JC1401 900

上海市科学技术委员会 14JC1402200

详细信息
    作者简介:

    占国华  上海大学机电工程与自动化学院硕士研究生.主要研究方向为网络化先进控制.E-mail:guohua361108@163.com

    李汪佩   上海大学机电工程与自动化学院硕士研究生.主要研究方向为机器视觉及网络化先进控制.E-mail:lwp15971862501@163.com

    费敏锐  上海大学机电工程与自动化学院教授.主要研究方向为网络化控制系统及实现.E-mail:mrfei@stafi.shu.edu.cn

    周文举   上海大学机电工程与自动化学院特聘研究员.主要研究方向为机器视觉及网络化先进控制.E-mail:zhouwenju2004@126.com

    通讯作者:

    杜大军     上海大学机电工程与自动化学院教授.主要研究方向为机器视觉与网络化先进控制.本文通信作者.E-mail:ddj@shu.edu.cn

Research of Visual H Control of Inverted Pendulum With Time-varying Computational Time and Computational Error

Funds: 

National Natural Science Foundation of China 61633016

National Natural Science Foundation of China 61773253

National Natural Science Foundation of China 61473182

Science and Technology Commission of Shanghai Municipality 15JC1401 900

Science and Technology Commission of Shanghai Municipality 14JC1402200

More Information
    Author Bio:

      Master student at the School of Mechatronics Engineering and Automation, Shanghai University. His main research interest is advanced control for networked control systems

      Master student at the School of Mechatronics Engineering and Automation, Shanghai University. His research interest covers machine vision and advanced control for networked control systems

      Professor at the School of Mechatronics Engineering and Automation, Shanghai University. His research interest covers networked control system and its implementation

      Specially-appointed researcher at the School of Mechatronics Engineering and Automation, Shanghai University. His research interest covers machine vision and advanced control for networked control systems

    Corresponding author: DU Da-Jun   Professor at the School of Mechatronics Engineering and Automation, Shanghai University. His research interest covers machine vision and advanced control for networked control systems. Corresponding author of this paper
  • 摘要: 针对基于视觉传感的倒立摆实时控制系统中,通过每帧图像计算小车位移和摆杆偏角产生的时变计算时间和计算误差直接影响控制系统性能甚至导致系统失稳问题,不同于目前不考虑计算时间和计算误差或将计算时间视为定时滞进行研究倒立摆视觉实时控制方法,本文首先创新设计了新型的倒立摆视觉伺服控制实验平台,然后设计了一种基于事件触发机制的工业图像采集策略,提出了考虑小车和摆杆特征的小车位移和摆杆偏角计算方法,并统计分析了图像处理计算时间和计算误差特性;进一步建立了融合计算时间和计算误差的闭环控制系统模型,理论证明系统的稳定性并建立了反映计算时间与系统稳定性能之间关系,给出了系统对计算误差的H扰动抑制水平γ和控制器设计方法.最后,仿真和实时控制实验验证了所提方法可行且有效.
    1)  本文责任编委 侯增广
  • 图  1  倒立摆视觉伺服控制实验平台结构

    Fig.  1  Scheme of inverted pendulum visual servoing control platform

    图  2  倒立摆视觉伺服控制系统控制框图

    Fig.  2  Control block diagram of inverted pendulum visual servoing control system

    图  3  视觉传感测量过程

    Fig.  3  Process of vision sensing measurement

    图  4  小车和摆杆局部定位

    Fig.  4  Local location of cart and pendulum

    图  5  小车和摆杆边缘信息

    Fig.  5  Edge information of cart and pendulum

    图  6  相机透视投影模型

    Fig.  6  The camera perspective projection model

    图  7  行扫描检测小车位移

    Fig.  7  Cart position is determined using line scan algorithm

    图  8  霍夫变换检测摆杆偏角

    Fig.  8  Pendulum angle is determined using Hough transform

    图  9  计算时间

    Fig.  9  Computational time

    图  10  小车位移计算误差统计

    Fig.  10  Computational error statistics of cart position

    图  11  小车速度计算误差统计

    Fig.  11  Computational error statistics of cart velocity

    图  12  摆杆偏角计算误差统计

    Fig.  12  Computational error statistics of pendulum angle

    图  13  摆杆角速度误差统计

    Fig.  13  Computational error statistics of pendulum angular velocity

    图  14  信号时序图

    Fig.  14  Signal timing diagram

    图  15  实验平台

    Fig.  15  Experimental platform

    图  16  在控制律${K_1}$下的小车位移和摆杆偏角(仿真)

    Fig.  16  Cart position and pendulum angle in controller ${K_1}$ (simulation)

    图  17  在控制律${K_2}$下的小车位移和摆杆偏角(仿真)

    Fig.  17  Cart position and pendulum angle in controller ${K_2}$ (simulation)

    图  18  在控制律${K_1}$下的小车位移和摆杆偏角(实时控制)

    Fig.  18  Cart position and pendulum angle in controller ${K_1}$ (real-time control)

    图  19  不同图像处理计算时间上界$\bar d$的小车位移

    Fig.  19  Cart position in different upper bound of image processing computational time $\bar d$

    图  20  不同图像处理计算时间上界$\bar d$的摆杆偏角

    Fig.  20  Pendulum angle in different upper bound of image processing computational time $\bar d$

    表  1  相机内部参数

    Table  1  Intrinsic parameters of camera

    参数 取值
    $f$ 909.5 pixels
    $d$ 0.9263 m
    ${\alpha _u}$ $1.6241\times 106 $ pixels/m
    ${\alpha _v}$ $1.6241\times106 $ pixels/m
    $s$ 0
    ${u_0}$ 334.85 pixels
    ${v_0}$ 267.46 pixels
    下载: 导出CSV
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  • 收稿日期:  2017-07-18
  • 录用日期:  2017-10-20
  • 刊出日期:  2019-02-20

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