Scara机器人关节摩擦建模与补偿的实验与仿真

doi:10.16182/j.issn1004731x.joss.17-0269

系统仿真学报 ›› 2019, Vol. 31 ›› Issue (8): 1572-1581.doi: 10.16182/j.issn1004731x.joss.17-0269

Scara机器人关节摩擦建模与补偿的实验与仿真

李琳, 林燕龙, 邹焱飚

华南理工大学机械与汽车工程学院机械学系,广东广州 510000

收稿日期:2017-06-06 修回日期:2017-07-25 发布日期:2019-12-12
作者简介:李琳(1962-),女,天津,博士,教授,硕导,研究方向为工业机器人、机器视觉。
基金资助:
国家科技重大专项资助项目(2015ZX04005 006-03),广东省科技重大专项(2014B090921004),广州市科技重大专项(2014Y2-00014)

Simulation and Experiment of Friction Modeling and Compensation of Scara

Li Lin, Lin Yanlong, Zou Yanbiao

College of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510000, China

Received:2017-06-06 Revised:2017-07-25 Published:2019-12-12

摘要/Abstract

摘要： 针对关节摩擦力引起Scara机器人定位精度变差的问题,对机器人关节摩擦力进行建模、辨识和补偿。提出了一种可用于工作空间受限机器人的摩擦力辨识方法,使用Lugre摩擦模型对机器人关节摩擦力进行描述 ,通过让机器人跟踪正弦曲线,建立摩擦力矩与关节速度的映射关系, 并对其摩擦参数进行辨识。设计了自适应控制方法对机器人进行控制。利用Scara机器人进行实验验证与仿真,仿真结果表明辨识得到的摩擦参数具有较高的精度。实验结果表明所提出的自适应控制方法能有效提高机器人的关节定位精度和大幅减小机器人末端加速度。

关键词: LuGre摩擦模型, 摩擦参数辨识方法, 自适应控制, 定位精度, Scara机器人

Abstract: Due to the friction of joints, the localization accuracy of Scara robot is deteriorated. To deal with this problem, the friction of robot joints is modeled, identified and compensated. A method of identifying the friction force of robot working in limited working space is proposed. The Lugre friction model is used to describe the joint friction of the robots. By allowing the robot to track the sinusoidal curve, the relationship between the friction torque and the joint velocity is established, and the friction parameters are identified. The adaptive control method is proposed to control the robot. The experiment and simulation are carried out on Scara robot. Compared with the simulation results, which shows that the friction parameters identified have high accuracy. The experimental results show that the proposed adaptive control method can effectively improve the joint localization accuracy of the robot and significantly reduce the acceleration of robot end.

Key words: lugre friction model, method of friction parameters identification, adaptive control, positioning accuracy, scara robot

中图分类号:

TP242.2

李琳, 林燕龙, 邹焱飚. Scara机器人关节摩擦建模与补偿的实验与仿真[J]. 系统仿真学报, 2019, 31(8): 1572-1581.

Li Lin, Lin Yanlong, Zou Yanbiao. Simulation and Experiment of Friction Modeling and Compensation of Scara[J]. Journal of System Simulation, 2019, 31(8): 1572-1581.

参考文献

[1] 杨成文. 平面关节机器人研制及其轨迹规划[D]. 广州: 华南理工大学, 2012.
Yang Chengwen.Research and Development of the SCARA Industrial Robot and Trajectory planning[D]. Guangzhou: South China University of Technology, 2012.
[2] 李长峰. 工业机器人发展趋势及在3C电子制造业的应用[J]. 机器人技术与应用, 2015(6): 37-38.
Li Changfeng.The Development Trend of Industrial Robot and its Application in 3C Electronics Manufacturing[J]. Robot Technique and Application, 2015(6): 37-38.
[3] 王田苗, 陶永. 我国工业机器人技术现状与产业化发展战略[J]. 机械工程学报, 2014, 50(9): 1-13.
Wang Tianmiao, Tao Yong.Research Status and Industrialization Development Strategy of Chinese Industrial Robot[J]. Journal of Mechanical Engineering, 2014, 50(9): 1-13.
[4] 朱世强, 吴文祥, 王宣银, 等. 考虑摩擦的谐波驱动机器人低速运动控制方法[J]. 农业机械学报, 2013, 44(11): 293-299.
Zhu Shiqiang, Wu Wenxiang, Wang Xuanyin, et al.Slow Motion Control of Serial Robots with Harmonic Drives Considering Friction Compensation[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(11): 293-299.
[5] 丁千, 翟红梅. 机械系统摩擦动力学研究进展[J]. 力学进展, 2013, 43(1): 112-131.
Ding Qian, Zhai Hongmei.The Advance in Reasearches of Friction Dynamics in Mechanics System[J]. Adances in Mechanics, 2013, 43(1): 112-131.
[6] Canudas de Wit C, Olsson H, Åström K J, et al. A new model for control of systems with friction[J]. IEEE Transactions on Automatic Control (S0018-9286), 1995, 40(3): 419-425.
[7] Vakil M, Fotouhi R, Nikiforu P N.Energy-based approach for friction identification of robotic joints[J]. Mechatronics (S0957-4158), 2011, 21(3): 614-624.
[8] Myo T S A, Ryo K, Motoji Y. Friction compensation of geared actuators with high presliding stiffness[J]. Journal of Dynamic Systems Measurement & Control (S0022-0434), 2015, 137(1): 011007
[9] Masayoshi I, Ryo K.An identification procedure for rate dependency of friction in robotic joints with limited motion ranges[J]. Mechatronics (S0957-4158), 2016, 36: 36-44.
[10] Kermani M R, Patel R V, Moallem M.Friction Identification and Compensation in Robotic Manipulators[J]. IEEE Transactions on Instrumentation & Measurement (S0018-9456), 2007, 56(6): 2346-2353.
[11] 刘海涛. 工业机器人的高速高精度控制方法研究[D]. 广州: 华南理工大学, 2012.
Liu Haitao.Research on High-speed and High-precision Control of Industrial Robots[D]. Guangzhou: South China University of Technology, 2012.
[12] 于昊. SCARA机器人参数自适应与补偿控制研究[D]. 哈尔滨: 哈尔滨工业大学, 2016.
Yu Hao.Research on Parameter Adaption and Compensation Control of SCARA Robot [D]. Harbin: Harbin Institute of Technology, 2016.
[13] 陈辞. 具有执行器非线性和状态约束的机器人自适应控制[D]. 广州: 广东工业大学, 2016.
Chen Ci.Adaptive Control of Robotic Systems with Actuator Nonlinearities and Motion Constraints [D]. Guangzhou: Guangdong University of Technology, 2016.
[14] 吴文祥, 朱世强, 王宣银, 等. 基于摩擦模糊建模与补偿的机器人低速控制[J]. 电机与控制学报, 2013, 17(8): 70-77.
Wu Wenxiang, Zhu Shiqiang, Wang Xuanyin, et al.Slow motion control of serial robots with friction compensation based on fuzzy logic system[J]. Electric Machines and Control, 2013, 17(8): 70-77.
[15] Bliman P A.Mathematical study of the Dahl’s friction Model[J]. Eur. J. Mech (S0997-7538), 1992, 11(6): 835-848.
[16] Hensen R H A, Molengraft M, Steinbuch M. Frequency domain identification of dynamic friction model parameters[J]. IEEE Transaction on Control Systems Technology (S1063-6536), 2002, 10(2): 191-196.
[17] Zhu Y, Pagilla P R.Static and dynamic friction compensation in trajectory tracking control of robots[C]. IEEE International Conference on Robotics & Automation, IEEE, 2002.

Scara机器人关节摩擦建模与补偿的实验与仿真

Simulation and Experiment of Friction Modeling and Compensation of Scara

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 7

编辑推荐

Metrics

本文评价

[1]	崔丽珍, 王巧利, 郭倩倩, 杨勇. 井下基于动态指纹更新的指纹定位算法研究[J]. 系统仿真学报, 2021, 33(4): 818-824.
[2]	王旭光, 张钦, 苏杰. 基于Radon变换的数字图像角点定位[J]. 系统仿真学报, 2019, 31(10): 2164-2173.
[3]	周颖, 陈阳, 岳彬. 改进的模型参考自适应在磨矿过程中的应用[J]. 系统仿真学报, 2018, 30(4): 1608-1614.
[4]	贺军, 骆敏舟, 赵江海, 徐林森, 李涛. 冗余度机器人变负载预测模糊自适应滑模控制[J]. 系统仿真学报, 2018, 30(3): 994-1001.
[5]	陈兵, 黄媛媛, 尹忠俊. 输流管道振动自适应控制算法鲁棒特性研究[J]. 系统仿真学报, 2016, 28(6): 1445-1452.
[6]	吴云洁, 宋闯, 左京兴. 低空飞行时改进的自适应鲁棒滑模姿态控制器[J]. 系统仿真学报, 2015, 27(9): 2163-2168.
[7]	龙浩, 宋述杰. 具有自修复功能自适应飞行控制系统仿真研究[J]. 系统仿真学报, 2015, 27(11): 2791-2796.