EI、Scopus 收录
中文核心期刊
Quick Search Issue Search Advanced Search
Volume 57 Issue 1
Jan.  2025
Turn off MathJax
Article Contents
Abstract
References
Related Articles
Xie Xingbiao, Zhang Xiaoxu, Sun Xiuting, Xu Jian. A new method for dynamic model identification and driving torque estimation for 6-PSU parallel robots. Chinese Journal of Theoretical and Applied Mechanics, 2025, 57(1): 183-198. DOI: 10.6052/0459-1879-24-416
Citation: Xie Xingbiao, Zhang Xiaoxu, Sun Xiuting, Xu Jian. A new method for dynamic model identification and driving torque estimation for 6-PSU parallel robots. Chinese Journal of Theoretical and Applied Mechanics, 2025, 57(1): 183-198. DOI: 10.6052/0459-1879-24-416
shu

A NEW METHOD FOR DYNAMIC MODEL IDENTIFICATION AND DRIVING TORQUE ESTIMATION FOR 6-PSU PARALLEL ROBOTS

  • *.

    Academy for Engineering and Technology, Fudan University, Shanghai 200433, China

  • †.

    MOE Engineering Research Center of AI & Robotics, Fudan University, Shanghai 200433, China

  • **.

    School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China

  • Received Date: August 26, 2024
  • Accepted Date: November 27, 2024
  • Available Online: November 27, 2024
  • Published Date: November 28, 2024
    Graphical Abstract
    • Abstract
  • Parallel robots often encounter motion singularities, which can lead to motor drive torque overload, causing overheating and reduced lifespan of the drive motors. Therefore, it is necessary to develop a method for accurately estimating the robot's drive torque based on the preset trajectory to reduce the failure rate of the drive motors. This paper takes the 6-PSU type parallel robot as the research object and proposes a solution for accurately estimating drive torque based on precise dynamic modeling and parameter identification. First, by considering the effects of ball screw modules and motor friction and inertia, and combining the Kane method, an inverse dynamics model for the resolution of the servo motor drive torque is established, resulting in an identifiable model corresponding to the minimum identifiable parameter set. To improve the accuracy and speed of the identification model for actual working conditions, in terms of end output trajectory optimization, viscous friction, and Coulomb friction are considered to reduce the condition number of the observation matrix of the identification model; in terms of structure, the symmetry of the linkage section is considered, and the linkage inertia that can be ignored is discovered, resulting in a simpler identification model. Using this model, a drive torque equation is constructed, which is used to estimate the driving force accurately. A physical simulation model of the robot was built using Simulink/Multibody, and inverse dynamics simulation experiments were conducted. The drive force estimation accuracy and noise resistance of the drive torque equations constructed by the identifiable model of the minimum identifiable parameter set and the simplified identification model obtained above were quantitatively analyzed. Finally, experiments were conducted on the 6-PSU type parallel robot platform, and the results show that the simplified drive torque equation proposed in this paper greatly simplifies the model complexity while ensuring the same estimation accuracy, which has a clear engineering value.
    • FullText(HTML)
    • References (31)
  • [1]
    Nabavi SN, Akbarzadeh A, Enferadi J. Closed-form dynamic formulation of a general 6-PUS robot. Journal of Intelligent & Robotic Systems, 2019, 96: 317-330
    [2]
    Liu X, Qi CK, Lin JF, et al. An actuation acceleration-based kinematic modeling and parameter identification approach for a six-degrees-of-freedom 6-PSU parallel robot with joint clearances. Journal of Mechanisms and Robotics, 2025, 17(1) : 011005
    [3]
    Theingi I, Chen M, Angeles J, et al. Management of parallel-manipulator singularities using joint-coupling. Advanced Robotics, 2007, 21(5-6): 583-600 doi: 10.1163/156855307780108231
    [4]
    Conconi M, Carricato M. A new assessment of singularities of parallel kinematic chains. IEEE Transactions on Robotics. 2009, 25(4): 757-770
    [5]
    Di Gregorio R. Instantaneous kinematics and singularity analysis of spatial Multi-DOF mechanisms based on the locations of the instantaneous screw axes. Mechanism and Machine Theory, 2024, 196: 105586 doi: 10.1016/j.mechmachtheory.2024.105586
    [6]
    Gosselin C, Angeles J. Singularity analysis of closed-loop kinematic chains. IEEE Transactions on Robotics and Automation, 1990, 6(3): 281-290
    [7]
    Ceccarelli M. Fundamentals of Mechanics of Robotic Manipulation. 2nd ed. Cham, Switzerland: Springer, 2022
    [8]
    Staicu S. Dynamics of Parallel Robots. Cham, Switzerland: Springer International Publishing, 2019
    [9]
    Sun T, Sun JR, Lian BB, et al. Sensorless admittance control of 6-DoF parallel robot in human-robot collaborative assembly. Robotics and Computer-Integrated Manufacturing, 2024, 88: 102742 doi: 10.1016/j.rcim.2024.102742
    [10]
    Farhat N, Mata V, Page Á, et al. Identification of dynamic parameters of a 3-DOF RPS parallel manipulator. Mechanism and Machine Theory, 2008, 43(1): 1-17 doi: 10.1016/j.mechmachtheory.2006.12.011
    [11]
    Gnad D, Gattringer H, Müller A, et al. Dedicated dynamic parameter identification for Delta-like robots. IEEE Robotics and Automation Letters, 2024, 9(5): 4393-4400 doi: 10.1109/LRA.2024.3380924
    [12]
    Kim TH, Kim Y, Kwak T, et al. Metaheuristic identification for an analytic dynamic model of a Delta robot with experimental verification. Actuators, MDPI, 2022, 11(12): 352 doi: 10.3390/act11120352
    [13]
    Wu J, Wang JS, You Z. An overview of dynamic parameter identification of robots. Robotics and Computer-Integrated Manufacturing, 2010, 26(5): 414-419 doi: 10.1016/j.rcim.2010.03.013
    [14]
    Zhou Z, Gosselin C. Simplified inverse dynamic models of parallel robots based on a Lagrangian approach. Meccanica, 2024, 59(4): 657-680 doi: 10.1007/s11012-024-01782-6
    [15]
    沈耀辉, 张学祥, 王若冰等. 6-UPS并联机器人动力学参数辨识. 机械设计与制造工程, 2023, 52(3): 20-26 (Shen Yaohui, Zhang Xuexiang, Wang Ruobing, et al. Dynamic parameter identification of a 6-UPS parallel robot. Machine Design and Manufacturing Engineering, 2023, 52(3): 20-26 (in Chinese)

    Shen Yaohui, Zhang Xuexiang, Wang Ruobing, et al. Dynamic parameter identification of a 6-UPS parallel robot. Machine Design and Manufacturing Engineering, 2023, 52(3): 20-26 (in Chinese)
    [16]
    李远慧, 程志林, 田体先. 六自由度并联平台惯性参数辨识方法. 机械设计与制造, 2024, 6: 305-308, 314 (Li Yuanhui , Cheng Zhilin , Tian Tixian. Inertial parameter identification method of six-degree-of-freedom parallel platform. Machinery Design & Manufacture, 2024, 6: 305-308, 314 (in Chinese)

    Li Yuanhui , Cheng Zhilin , Tian Tixian. Inertial parameter identification method of six-degree-of-freedom parallel platform. Machinery Design & Manufacture, 2024, 6: 305-308, 314 (in Chinese)
    [17]
    Chen CT, Renn JC, Yan ZY. Experimental identification of inertial and friction parameters for electro-hydraulic motion simulators. Mechatronics, 2011, 21(1): 1-10 doi: 10.1016/j.mechatronics.2010.07.012
    [18]
    孔令富, 张世辉, 肖文辉等. 基于牛顿—欧拉方法的6-PUS并联机构刚体动力学模型. 机器人, 2004, 5: 395-399 (Kong Lingfu, Zhang Shihui, Xiao Wenhui, et al. Rigid body dynamics model of the 6-PUS parallel mechanism based on Newton-Euler method. Robot, 2004, 5: 395-399 (in Chinese)

    Kong Lingfu, Zhang Shihui, Xiao Wenhui, et al. Rigid body dynamics model of the 6-PUS parallel mechanism based on Newton-Euler method. Robot, 2004, 5: 395-399 (in Chinese)
    [19]
    侯立果, 王丹, 安大卫等. 多维力加载装置动力学建模及加载试验. 北京航空航天大学学报, 2018, 44(5): 1095-1101 (Hou Lihuo, Wang Dan, An Dawei, et al. Dynamic modeling and loading experiment of multi-dimensional loading device. Journal of Beijing University of Aeronautics and Astronsutics, 2018, 44(5): 1095-1101 (in Chinese)

    Hou Lihuo, Wang Dan, An Dawei, et al. Dynamic modeling and loading experiment of multi-dimensional loading device. Journal of Beijing University of Aeronautics and Astronsutics, 2018, 44(5): 1095-1101 (in Chinese)
    [20]
    Swevers J, Ganseman C, Tukel DB, et al. Optimal robot excitation and identification. IEEE Transactions on Robotics and Automation, 1997, 13(5): 730-740 doi: 10.1109/70.631234
    [21]
    Park KJ. Fourier-based optimal excitation trajectories for the dynamic identification of robots. Robotica, 2006, 24(5): 625-633 doi: 10.1017/S0263574706002712
    [22]
    Tu X, Zhao P, Zhou YF. Parameter identification of static friction based on an optimal exciting trajectory. IOP Conference Series: Materials Science and Engineering, 2017, 280(1): 012025
    [23]
    Hao L, Pagani R, Beschi M, et al. Dynamic and friction parameters of an industrial robot: Identification, comparison and repetitiveness analysis. Robotics, 2021, 10(1): 49 doi: 10.3390/robotics10010049
    [24]
    Lee T, Lee BD, Park FC. Optimal excitation trajectories for mechanical systems identification. Automatica, 2021, 131(6): 109773
    [25]
    Tian HY, Huber M, Mower CE, et al. Excitation trajectory optimization for dynamic parameter identification using virtual constraints in Hands-on robotic system//2024 IEEE International Conference on Robotics and Automation, Yokohama, Japan. Piscataway, NJ: IEEE, 2024: 11605-11611
    [26]
    Cheng J, Bi SS, Yuan C. Dynamic parameters identification method of 6-DOF industrial robot based on quaternion. Mathematics, 2022, 10(9): 1513 doi: 10.3390/math10091513
    [27]
    Gautier M, Poignet Ph. Extended Kalman filtering and weighted least squares dynamic identification of robot. Control Engineering Practice, 2001, 9(12): 1361-1372 doi: 10.1016/S0967-0661(01)00105-8
    [28]
    Vivas A, Poignet P, Marquet F, et al. Experimental dynamic identification of a fully parallel robot//2003 IEEE International Conference on Robotics and Automation, Taipei, Taiwan, China. Piscataway, NJ: IEEE, 2003, 3: 3278-3283
    [29]
    Guo XJ, Zhang L, Han Kai. Dynamic parameter identification of robot manipulators based on the optimal excitation trajectory//2018 IEEE International Conference on Mechatronics and Automation, Changchun, China. Piscataway, NJ: IEEE, 2018: 2145-2150
    [30]
    Li XJ, Gu JN, Sun XH, et al. Parameter identification of robot manipulators with unknown payloads using an improved chaotic sparrow search algorithm. Applied Intelligence, 2022, 52: 10341-10351
    [31]
    Mamedov S, Mikhel S. Practical aspects of model-based collision detection. Frontiers in Robotics and AI, 2020, 7: 571574
    • Related Articles

  • Related Articles

    [1]Zhou Rui, Xiong Yukai, Chu Jielei, Kan Qianhua, Kang Guozheng, Zhang Xu. PARAMETER IDENTIFICATION OF NONLOCAL CRYSTAL PLASTIC MODEL BASED ON MACHINE LEARNING AND GENETIC ALGORITHM[J]. Chinese Journal of Theoretical and Applied Mechanics, 2024, 56(3): 751-762. DOI: 10.6052/0459-1879-23-479
    [2]Wei Chang, Fan Yuchen, Zhou Yongqing, Liu Xin, Zhang Chaoqun, Wang Heyang. MULTI-OUTPUT PHYSICS-INFORMED NEURAL NETWORKS MODEL BASED ON THE RUNGE-KUTTA METHOD[J]. Chinese Journal of Theoretical and Applied Mechanics, 2023, 55(10): 2405-2416. DOI: 10.6052/0459-1879-23-299
    [3]Wei Xinyu, Sang Jianbing, Zhang Ruilin, Wang Jingyuan, Liu Baoyou. TIME-DEPENDENT MECHANICAL BEHAVIOR AND CONSTITUTIVE PARAMETER IDENTIFICATION OF CHONDROCYTES BASED ON MACHINE LEARNING[J]. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3215-3222. DOI: 10.6052/0459-1879-22-344
    [4]Duan Shuyong, Duan Haodong, Han Xu, Li Changluo, Ouyang Heng, Li Yule, Liu Guirong. INVERSE OF KEY PARAMETERS OF NONLINEAR FRICTION MODEL OF ROBOT JOINTS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3189-3202. DOI: 10.6052/0459-1879-22-252
    [5]Fei Qingguo, Jiang Dong, Chen Sufang, Qin Furong. THERMAL-RELATED PARAMETER IDENTIFICATION OF BRAIDED COMPOSITES AT HIGH TEMPERATURE[J]. Chinese Journal of Theoretical and Applied Mechanics, 2018, 50(3): 497-507. DOI: 10.6052/0459-1879-18-078
    [6]Niu Wendong, Wang Yanhui, Yang Yanpeng, Zhu Yaqiang, Wang Shuxin. HYDRODYNAMIC PARAMETER IDENTIFICATION OF HYBRID-DRIVEN UNDERWATER GLIDER[J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(4): 813-822. DOI: 10.6052/0459-1879-16-162
    [7]Qu Jie, Qin Wei, Jin Quanlin. STUDY ON THE PARAMETER VALUE DOMAIN OF MACRO-MICRO CONSTITUTIVE MODEL[J]. Chinese Journal of Theoretical and Applied Mechanics, 2014, 46(6): 920-930. DOI: 10.6052/0459-1879-14-049
    [8]Xie Yong, Liu Pan, Cai Guoping. PARAMETER IDENTIFICATION OF FLEXIBLE PLATE BASED ON THE ACCELERATION OUTPUT[J]. Chinese Journal of Theoretical and Applied Mechanics, 2014, 46(1): 128-135. DOI: 10.6052/0459-1879-13-124
    [9]A FLUID DYNAMICS MODEL FOR THE LOW SPEED TRAFFIC SYSTEMS[J]. Chinese Journal of Theoretical and Applied Mechanics, 1994, 26(2): 149-157. DOI: 10.6052/0459-1879-1994-2-1995-532
    [10]AN INVESTIGATION INTO THE FIELD IDENTIFICATION TECHNIQUE OF MODAL PARAMETERS OF ROTATING SYSTEM[J]. Chinese Journal of Theoretical and Applied Mechanics, 1991, 23(5): 634-640. DOI: 10.6052/0459-1879-1991-5-1995-886

  • Cited by

    Periodical cited type(4)

    1. 陈伟，张奇志，周亚丽. 组合弹性无缘轮半被动行走的混沌和同步分析. 力学季刊. 2024(01): 132-143 .
    2. 党霞. 基于引力势场的包装机器人自动避障控制方法. 包装工程. 2021(21): 254-259 .
    3. 朱诗慧，周震，吕敬，王琪. 三相驱动下非光滑振动驱动系统的动力学分析. 力学学报. 2020(06): 1755-1764 . 本站查看
    4. 王二虎，丁旺才，李国芳，郭建宏. 小型电磁振动驱动器的设计与参数匹配分析. 机械科学与技术. 2018(07): 1022-1026 .

    Other cited types(4)

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (140) PDF downloads (38) Cited by(8)
    Related

    Download Center

    Author Center

      Copyright © Editorial Office of the Chinese Journal of Mechanics   京ICP备05039218号-1

      Address：15 Beishihuan Xi Lu, Haidian District, Beijing, China   China Pos：100190

      Tel：010-62536271

      Email：lxxb@cstam.org.cn

      Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return