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深海起重机系统的实时轨迹规划方法

王岳 孙宁 吴易鸣 梁潇 陈鹤 方勇纯

王岳, 孙宁, 吴易鸣, 梁潇, 陈鹤, 方勇纯. 深海起重机系统的实时轨迹规划方法. 自动化学报, 2020, 46(x): 1−10 doi: 10.16383/j.aas.c200262
引用本文: 王岳, 孙宁, 吴易鸣, 梁潇, 陈鹤, 方勇纯. 深海起重机系统的实时轨迹规划方法. 自动化学报, 2020, 46(x): 1−10 doi: 10.16383/j.aas.c200262
Wang Yue, Sun Ning, Wu Yi-Ming, Liang Xiao, Chen He, Fang Chun-Yong. Real-time motion planning of deep sea-oriented flexible crane systems. Acta Automatica Sinica, 2020, 46(x): 1−10 doi: 10.16383/j.aas.c200262
Citation: Wang Yue, Sun Ning, Wu Yi-Ming, Liang Xiao, Chen He, Fang Chun-Yong. Real-time motion planning of deep sea-oriented flexible crane systems. Acta Automatica Sinica, 2020, 46(x): 1−10 doi: 10.16383/j.aas.c200262

深海起重机系统的实时轨迹规划方法

doi: 10.16383/j.aas.c200262
基金项目: 国家自然科学基金项目(U1706228, 61873134), 国家重点研发计划项目(2018YFB1309000)资助
详细信息
    作者简介:

    王岳:南开大学机器人与信息自动化研究所硕士研究生. 主要研究方向包括欠驱动控制系统. E-mail: yuew@mail.nankai.edu.cn

    孙宁:南开大学机器人与信息自动化研究所副教授, 博士生导师. 主要研究方向包括欠驱动机器人(包括各类吊车)、气动人工肌肉等系统的控制及应用研究. 本文通信作者. E-mail: sunn@nankai.edu.cn

    吴易鸣:南开大学机器人与信息自动化研究所博士研究生. 主要研究方向包括欠驱动控制系统. E-mail: ymwu@mail.nankai.edu.cn

    梁潇:南开大学机器人与信息自动化研究所讲师. 主要研究方向包括无人机系统的运动规划和非线性控制. E-mail: liangx@nankai.edu.cn

    陈鹤:河北工业大学人工智能与数据科学学院讲师. 主要研究方向包括机电一体化控制、桥式起重机和轮式移动机器人. E-mail: chenh@hebut.edu.cn

    方勇纯:南开大学机器人与信息自动化研究所教授. 主要研究方向包括非线性控制、视觉伺服、欠驱动系统控制和基于原子力显微镜的纳米系统. E-mail: fangyc@nankai.edu.cn

Real-time Motion Planning of Deep Sea-oriented Flexible Crane Systems

Funds: Supported by the National Natural Science Foundation of China (U1706228, 61873134) and the National Key R&D Program of China (2018YFB1309000)
  • 摘要: 近年来, 随着海洋资源的不断开发与海洋工程的全球化推进, 深海起重机得到了广泛应用, 其控制问题也引起研究人员的极大关注. 在深海作业环境中, 由于吊运过程受到水流作用力的影响, 负载摆动幅度增大, 系统状态量间非线性耦合关系增强, 使系统控制难度加大. 为此, 本文针对深海起重机系统提出了一种实时轨迹规划方法. 具体而言, 通过分析系统动力学特性和状态变量之间复杂的耦合关系, 提出了一种实时规划轨迹的方法, 并从理论上证明了该方法可在使台车准确快速到达指定位置的同时, 有效抑制负载摆动. 最后, 一系列仿真结果证明了所提方法的良好性能.
  • 图  1  深海柔性起重机系统

    Fig.  1  The flexible deep sea crane system

    图  2  实时轨迹规划示意图

    Fig.  2  Schematic diagram of real-time trajectory planning

    图  3  参考位移、速度、加速度轨迹

    Fig.  3  The reference displacement, velocity, and acceleration trajectories

    图  4  仿真对比结果

    Fig.  4  Comparison results

    图  6  含初始扰动的仿真对比结果

    Fig.  6  imulation results with initial disturbance

    图  7  含中间扰动的仿真对比结果

    Fig.  7  Simulation results with intermediate disturbance

    图  8  验证所提方法实时性的仿真结果

    Fig.  8  Simulation results to verify the real-time performance of the proposed method

    图  9  与输入整形方法的仿真对比结果

    Fig.  9  Simulation results compared with input shaping method

    图  5  负载摆动三维仿真图

    Fig.  5  Three-dimensional diagram of the vibration $ w(y,t) $

    表  1  系统参数

    Table  1  System parameters

    参数 物理意义 单位
    $m_r$ 负载质量 kg
    $m_t$ 台车质量 kg
    $d$ 负载截面直径 m
    $l$ 负载长度 m
    $E$ 杨氏模量 GPa
    $c$ 粘性阻尼系数 N·s/m
    $\rho_w$ 水密度 kg/m3
    $C_a$ 附加质量系数 -
    $C_d$ 阻力系数 -
    下载: 导出CSV

    表  2  系统参数仿真值

    Table  2  Simulation values of system parameters

    参数 取值 单位
    $m_r$ 0.37 kg
    $m_t$ 38.0 kg
    $d$ 0.008 m
    $l$ 1 m
    $E$ 248.3 GPa
    $c$ 0.6 N·s/m
    $\rho_w$ 1000 kg/m3
    $C_a$ 0.93 -
    $C_d$ 1.28 -
    下载: 导出CSV

    表  3  无外部扰动时量化指标对比结果

    Table  3  Comparison results of quantitative indices without external disturbance

    定位参考轨迹 本文规划轨迹
    摆动幅度 –0.278 m –0.142 m
    反向摆动幅度 0.032 m 0.024 m
    进入相对稳态时间 3.7 s 3.1 s
    下载: 导出CSV

    表  4  与输入整形方法的量化指标对比结果

    Table  4  Comparison results of quantitative indices with input shaping method

    输入整形方法 本文规划方法
    摆动幅度 –0.183 m –0.142 m
    反向摆动幅度 0.052 m 0.024 m
    进入相对稳态时间 4.3 s 3.1 s
    下载: 导出CSV
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