吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (1): 52-62.doi: 10.13229/j.cnki.jdxbgxb.20231431

• 车辆工程·机械工程 • 上一篇    下一篇

聚变堆大型机械臂鲁棒自适应精度控制

左从菊1,2,3(),秦国栋1,潘洪涛1,程勇1,周浦城3,秦晓燕3,汪卫华1()   

  1. 1.中国科学院 合肥物质科学研究院 等离子体物理研究所，合肥 230031
    2.中国科学技术大学 科学岛分院，合肥 230026
    3.陆军炮兵和防空兵学院 信息工程系，合肥 230031
  • 收稿日期:2023-12-22 出版日期:2025-01-01 发布日期:2025-03-28
  • 通讯作者: 汪卫华 E-mail:judy@mail.ustc.edu.cn;whwang@ipp.ac.cn
  • 作者简介:左从菊（1979-），女，教授，博士.研究方向：聚变堆大型重载机器人控制系统.E-mail： judy@mail.ustc.edu.cn
  • 基金资助:
    国家自然科学基金项目(12305251);国家重大科技基础设施建设项目(2018-000052-73-01- 001228)

Robust adaptive accuracy control of large manipulator for fusion reactor

Cong-ju ZUO1,2,3(),Guo-dong QIN1,Hong-tao PAN1,Yong CHENG1,Pu-cheng ZHOU3,Xiao-yan QIN3,Wei-hua WANG1()   

  1. 1.Institute of Plasma Physics，Chinese Academy of Science，Hefei 230031，China
    2.University of Science and Technology of China，Hefei 230026，China
    3.Department of Information Engineering，Army Academy of Artillery and Air Defense，Hefei 230031，China
  • Received:2023-12-22 Online:2025-01-01 Published:2025-03-28
  • Contact: Wei-hua WANG E-mail:judy@mail.ustc.edu.cn;whwang@ipp.ac.cn

RICH HTML

 0   

PDF (PC)

106

摘要：

为了解聚变堆遥操作系统中的大型机械臂精确控制问题，提出了聚变堆大型机械臂鲁棒自适应精度控制研究。该研究基于Hamilton Jacobi方程设计一种鲁棒自适应滑模控制策略，抑制不确定性和时变参数对系统的影响，并通过Lyapunov理论证明控制器的稳定性。为解决刚柔耦合等非几何参数对大型机械臂造成的位置误差，提出了一种基于动态控制器的可变参数精度控制算法，融合工作空间网格化变参数原理进行参数辨识，可实现机械臂非几何参数误差补偿。实验结果表明，本文方法有效提高机械臂动态控制精度，抑制非几何参数影响。

关键词: 聚变堆, 大型机械臂, 鲁棒自适应, 变参数补偿, 精度控制

Abstract:

In order to solve the problem of precise control of large robotic arms in the remote operation system of fusion reactors， a study on robust adaptive precision control of large robotic arms in fusion reactors is proposed. This study designs a robust adaptive sliding mode control strategy based on the Hamilton Jacobi equation to suppress the influence of uncertainty and time-varying parameters on the system， and proves the stability of the controller through Lyapunov theory. To solve the position error caused by non geometric parameters such as rigid flexible coupling on large robotic arms， a variable parameter accuracy control algorithm based on dynamic controllers is proposed， which integrates the principle of workspace grid based variable parameters for parameter identification and can achieve non geometric parameter error compensation of robotic arms. The experimental results show that this method effectively improves the dynamic control accuracy of the robotic arm and suppresses the influence of non geometric parameters.

Key words: fusion reactor, large manipulator, robust adaptive, variable parameter compensation, accuracy control

中图分类号: 

  • TP241.3

图1

CMOR整体结构及维护示意图"

图2

CMOR关节分布及坐标系"

表1

CMOR D-H参数"

连杆变量转角位移/m范围
10(0,0,0)(d0,0,0)0~6 726 mm
2θ1(0,0,0)(1.76,0,0)-90°～90°
3θ2(90°,0,90°)(0,0,0)-90°～90°
4θ3(-90°,0,90°)(0.375,0,2.24)-180°～180°
5θ4(-90°,0,-90°)(0.375,0,0)0°～90°
6θ5(-90°,0,90°)(0,0,2.24)-180°～180°
7θ6(90°,0,0)(0,0,0)-90°～90°
8θ7(-90°,0,-90°)(0,0,1.65)-100°～100°
9θ8(0,0,0)(0,0,0)-90°～90°

图3

CMOR柔性连杆处理结果"

图4

CMOR柔性关节建模原理"

表2

CMOR各关节刚度值"

关节刚度
19.0×109 N·m/rad
28.6×109 N·m/rad
38.0×109 N·m/rad
48.0×109 N·m/rad
53.0×109 N·m/rad
64.0×109 N·m/rad
72.0×109 N·m/rad
83.0×109 N·m/rad

图5

CMOR鲁棒自适应控制原理"

图6

CMOR网格化变参数补偿原理"

图7

CMOR联合仿真程序"

表3

CMOR系统动力学参数"

关节质量/kg主惯量/（kg·m-2）质心/m
12 7393582（0.895，0，0）
2420163（0.37，0，0.074）
323746（-0.138， -0.064，0.67）
418177（0.33，0.308，0.07）
516816（0，0，0.78）
633199（0，0.426，0.144）
7614（0， -0.089，0.353）
816719（0.09，0.211，0.019）

图8

CMOR刚柔耦合仿真时序图"

图9

CMOR关节角度跟踪曲线及跟踪误差"

图10

负载0 kg时CMOR关节扭矩"

图11

CMOR末端空间位移与误差"

图12

不同负载下关节3的动态响应"

图13

CMOR末端空间位移与误差"

表4

CMOR 关节J3补偿参数 (rad)"

连杆负载=2 000 kg负载=1 000 kg负载=500 kg负载=0 kg
1-1.278×10-2-7.563 9×10-3-5.117 8×10-3-2.647 5×10-3
2-1.845×10-2-1.155 3×10-2-8.109 2×10-3-4.737 3×10-3
3-1.989×10-2-1.299 7×10-2-9.554 1×10-3-6.186 1×10-3
4-1.601×10-2-1.094 5×10-2-8.421 2×10-3-5.961 3×10-3
51.237 7×10-27.155 6×10-34.558 2×10-32.022 7×10-3
61.824×10-21.131 6×10-27.858 5×10-34.470 8×10-3
71.967 7×10-21.275 8×10-29.302 7×10-35.917 3×10-3
81.565 4×10-21.044 8×10-27.861 5×10-35.334 1×10-3

图14

CMOR 位置误差补偿结果"

1 李建刚. 聚变工程实验堆装置主机设计[M]. 北京:科学出版社, 2016.
2 Song Y T, Li J G, Wan Y X, et al. Engineering design of the CFETR machine[J]. Fusion Engineering and Design, 2022, 183: No.113247.
3 周振国. ITER MPD 旋转关节结构设计[D]. 西安:中国科学技术大学工程科学学院, 2018.
Zhou Zhen-guo. Structural design of ITER MPD rotary joint[D]. Xi'an: School of Engineering Science,University of Science and Technology of China, 2018.
4 Qin G D, Ji A H, Wang W, et al. Analyzing trajectory tracking accuracy of a flexible multi-purpose deployer[J]. Fusion Engineering and Design, 2020, 151: No.111396.
5 Manuelraj M S, Dutta P, Gotewal K K, et al. Structural analysis of ITER multi-purpose deployer[J]. Fusion Engineering and Design, 2016, 109: 1296-1301.
6 龙海波, 杨家其, 尹靓,等. 基于鲁棒优化的不确定需求下应急物资配送多目标决策模型[J].吉林大学学报工学版, 2023, 53(4): 1078-1084.
Long Hai-bo, Yang Jia-qi, Yin Liang, et al. Robust optimization-based multi-objective decision model for emergency material distribution under uncertain demand[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(4): 1078-1084.
7 王宏志,王婷婷,兰淼淼,等.基于位置跟踪的机械臂多电机新型滑模控制策略[J].吉林大学学报:工学版, 2024,54(5): 1443-1458.
Wang Hong-zhi, Wang Ting-ting, Lan Miao-miao, et al. A novel sliding mode control strategy for multi-motor of robotic arm based on position tracking[J]. Journal of Jilin University(Engineering and Technology Edition), 2024,54(5): 1443-1458.
8 周挺, 徐宇工, 吴斌. 球形机器人的自适应分数阶PI~λD~μ滑模速度控制方法[J].吉林大学学报工学版, 2021, 51(2): 728-737.
Zhou Ting, Xu Yu-gong, Wu Bin. Adaptive fractional order PI~λD~μ sliding mode velocity control method for spherical robots[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 728-737.
9 杨超, 郭佳, 张铭钧. 基于RBF神经网络的作业型AUV自适应终端滑模控制方法及实验研究[J].机器人, 2018, 40(3): 336-345.
Yang Chao, Guo Jia, Zhang Ming-jun. Adaptive terminal sliding mode control method based on RBF neural networkfor operational AUV and its experimental research[J]. Robot, 2018, 40(3): 336-345.
10 赵兴强, 刘振, 高存臣. 机械臂系统自适应神经网络滑模控制器设计[J]. 控制工程,2023, 30(9): 1624-1629.
Zhao Xing-qiang, Liu Zhen, Gao Cun-chen. Adaptive neural network-based sliding mode controller design for manipulator systems[J]. Control Engineering, 2023, 30(9): 1624-1629.
11 Alian A, Zareinejad M, Talebi H A. Curvature tracking of a two-segmented soft finger using an adaptive sliding-mode controller[J]. IEEE/ ASME Transactions on Mechatronics, 2022, 28(1): 50-59.
12 Cao G Q, Zhao X Y, Ye C L, et al. Fuzzy adaptive PID control method for multi mecanum wheeled mobile robot[J]. Journal of Mechanical Science and Technology, 2022, 36(4): 2019-2029.
13 Ding L, Niu L Z, Su Y, et al. Dynamic finite element modeling and simulation of soft robots[J]. Chinese Journal of Mechanical Engineering, 2022, 35(1): 1-11.
14 陈昊然, 张宇, 段昊宇翔, 等. 串联机器人模态仿真与实验[J].制造业自动化, 2023, 45(10): 115-119.
Chen Hao-ran, Zhang Yu, Duan Hao-yuxiang, et al. Modal simulation and experiment of series robot[J]. Manufacturing Automation, 2023, 45(10): 115-119.
15 高强.基于假设模态法的柔性机械臂瞬时变形响应分析[J].自动化与仪器仪表, 2019(12): 65-67.
Gao Qiang. Analysis of transient deformation response for flexible robotic manipulator using assumed mode method[J]. Automation and Instrumentation, 2019(12): 65-67.
16 Abele E, Weigold M, Rothenbücher S. Modeling and identification of an industrial robot for machining applications[J]. Annals-Manufacturing Technology, 2007, 56(1): 387-390.
17 张成新, 余跃庆. 具有关节柔性和臂柔性的机器人操作受限物体的动力学建模[J]. 机械工程学报, 2003, 39(6): 9-12.
Zhang Cheng-xin, Yu Yue-qing. Dynamic modeling of robot arm with joint and link flexibility manipulating a constrained object[J]. Journal of Mechanical Engineering, 2003, 39(6): 9-12.
18 刘娜. 煤矿焊接机器人刚柔耦合动力学与动态特性研究[D]. 北京:中国矿业大学机电与信息工程学院, 2018.
Liu Na. Research on rigid-flexible coupling dynamics and dynamic characteristics of welding robot for coal mines[D]. Beijing:School of Mechanical,Electrical and Information Engineering,China University of Mining and Technology, 2018.
19 Niu B, Zhao J. Stabilization and L2-gain analysis for a class of cascade switched nonlinear systems: An average dwell-time method[J]. Nonlinear Analysis: Hybrid Systems, 2011, 5(4): 671-680.
20 欧攀,尉青锋,陈末然. 基于振动特征的火炮身管打击精度控制仿真[J]. 计算机仿真, 2021,38(6): 18-21, 77.
Pan Ou, Wei Qing-Feng, Chen Mo-Ran. simulation of gun barrel strike precision control based on vibration characteristics[J]. Computer Simulation, 2021, 38(6): 18-21, 77.
21 Luo G Y, Zou L, Wang Z L, et al. A novel kinematic parameters calibration method for industrial robot based on levenberg-marquardt and differential evolution hybrid algorithm[J]. Robotics and Computer Integrated Manufacturing, 2021, 71: No.102165.
[1] 杨大鹏, 姜力, 赵京东，刘宏 . 基于脑电信号的高智能假手控制[J]. 吉林大学学报(工学版), 2008, 38(05): 1225-1230.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发