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

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

王岳^1,,
孙宁^1,,
吴易鸣^1,,
梁潇^1,,
陈鹤^2,,
方勇纯^1,

1.
南开大学人工智能学院机器人与信息自动化研究所, 天津市智能机器人技术重点实验室天津 300350
2.
河北工业大学人工智能与数据科学学院天津 300350

基金项目: 国家自然科学基金(U1706228, 61873134), 国家重点研发计划(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. 主要研究方向为欠驱动控制系统. 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教授. 主要研究方向为欠驱动机器人(包括各类吊车), 气动人工肌肉等系统的控制及应用. 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. 主要研究方向为欠驱动控制系统. 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. 主要研究方向为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. 主要研究方向为机电一体化控制, 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. 主要研究方向为非线性控制, 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

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出版历程
- 收稿日期: 2020-04-29
- 网络出版日期: 2021-10-27
- 刊出日期: 2021-12-23

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

WANG Yue^1
,,
SUN Ning^1
,,
WU Yi-Ming^1
,,
LIANG Xiao^1
,,
CHEN He^2
,,
FANG Yong-Chun^1
,

1.
Institute of Robotics and Automatic Information Systems (IRAIS), College of Artificial Intelligence, Tianjin Key Laboratory of Intelligent Robotics (tjKLIR), Nankai University, Tianjin 300350
2.
College of Artificial Intelligence, Hebei University of Technology, Tianjin 300350

Funds: Supported by National Natural Science Foundation of China (U1706228, 61873134) and National Key Research and Development Program of China (2018YFB1309000)

More Information

Author Bio:
WANG Yue　Master student at the Institute of Robotics and Automatic Information Systems, Nankai University. Her research interest covers control of underactuated systems

SUN Ning　Professor at the Institute of Robotics and Automatic Information Systems, Nankai University. His research interest covers control of underactuated robotic systems (including cranes), and pneumatic artificial muscle systems. Corresponding author of this paper

WU Yi-Ming　Ph.D. candidate at the Institute of Robotics and Automatic Information Systems, Nankai University. Her research interest covers control of underactuated systems

LIANG Xiao　Lecturer at the Institute of Robotics and Automatic Information System, Nankai University. His research interest covers motion planning and nonlinear control of unmanned aerial vehicle systems

CHEN He　Lecturer at the School of Artificial Intelligence, Hebei University of Technology. His research interest covers control of mechatronics, overhead cranes, and wheeled mobile robots

FANG Yong-Chun　Professor at the Institute of Robotics and Automatic Information Systems, Nankai University. His research interest covers nonlinear control, visual servoing, control of underactuated systems, and atomic force microscope (AFM)-based nano-systems

摘要

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.
- 深海起重机 /
- 欠驱动系统 /
- 实时轨迹规划 /
- 非线性耦合 /
- 摆动抑制
Abstract: In recent years, with the continuous exploitation of marine resources and the global development of marine engineering, deep sea-oriented crane systems have been widely used, and their control problems have also attracted great attention. Under the deep sea working environment, since the transportation process is influenced by the hydrodynamic force, the payload＇s vibration amplitude increases, and the nonlinear coupling relationship between state variables becomes stronger, making the control problem more challenging. To this end, this paper proposes a real-time trajectory planning method for the deep sea crane system. Specifically, by analyzing the dynamics and the complex coupling relationship between state variables, a real-time trajectory planning method is proposed, and it is theoretically proved that this method can achieve fast and accurate trolley positioning and effective cargo swing suppression. Finally, numerical simulation results indicate the satisfactory performance of the designed method.
- Deep sea-oriented crane /
- underactuated system /
- real-time trajectory planning /
- nonlinear coupling /
- anti-vibration

HTML全文

图 1 深海柔性起重机系统

Fig. 1 The flexible deep sea crane system

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图 2 实时轨迹规划示意图

Fig. 2 Schematic diagram of real-time trajectory planning

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图 3 参考位移、速度、加速度轨迹

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

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图 4 仿真对比结果

Fig. 4 Comparison results

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图 5 负载摆动三维仿真图

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

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图 6 含初始扰动的仿真对比结果

Fig. 6 Simulation results with initial disturbance

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图 7 含中间扰动的仿真对比结果

Fig. 7 Simulation results with intermediate disturbance

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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

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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

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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	—

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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	—

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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

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

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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

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

下载: 导出CSV

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