Trajectory Friction Compensation Algorithm for Robots Based on Velocity Control

被引:0
|
作者
Ye B. [1 ]
Li S. [1 ]
Tan S. [1 ]
Li X. [1 ]
Jin X. [1 ]
Shao B. [1 ]
机构
[1] School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Hubei, Wuhan
关键词
friction compensation; parameter identification; tracking differentiator; trajectory;
D O I
10.12141/j.issn.1000-565X.230368
中图分类号
学科分类号
摘要
Currently, robots are extensively utilized in industrial manufacturing. However, due to the influence of joint friction and other factors in the robot system, the robot trajectory tracking accuracy is difficult to meet the requirements of high-precision production. In this study, a friction compensation control algorithm in speed mode was proposed to mitigate the impact of non-linear friction factors in the mechanical structure and unmodelled disturbances on the robot’s operational stability and machining precision. The optimal excitation trajectory was designed by a combination of Fourier series and fifth-order polynomial. Dynamic parameters were then preidentified by the least squares method and iteratively optimized through the Levenberg-Marquardt method to establish a more precise robot dynamic model. Subsequently, the Lyapunov method was adopted to design the trajectory tracking control algorithm, and the joint angles collected in the steepest discrete tracking differentiator were fed into the control algorithm to calculate the real-time compensation. The compensation value was then applied in the robot, which effectively achieving friction compensation. The proposed algorithm was validated by employing a six-degree-of-freedom serial robot as an experimental subject. The results demonstrate that the trajectory tracking error is reduced by approximately 35%, as comparing with that under the non-compensation conditions, which confirms the efficacy of the algorithm in the realm of robot friction compensation. © 2024 South China University of Technology. All rights reserved.
引用
收藏
页码:51 / 58
页数:7
相关论文
共 15 条
  • [1] BHATT P M, Trajectory-dependent compensation scheme to reduce manipulator execution errors for manufacturing applications [C], Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, (2021)
  • [2] MARQUES F,, FLORES P,, CLARO J, Modeling and analysis of friction including rolling effects in multibody dynamics:a review [J], Multibody System Dynamics, 45, pp. 223-244, (2019)
  • [3] XIAO B, Observer-based control for robotic manipulations with uncertain kinematics and dynamics [C], Proceedings of 2016 IEEE the 14th International Workshop on Advanced Motion Control, pp. 282-288, (2016)
  • [4] Qiong WEI, JIAO Zongxia, WANG Jun, Control of pneumatic position servo with LuGre model-based friction compensation, Journal of Mechanical Engineering, 54, 20, pp. 131-138, (2018)
  • [5] LI Junyang, ZHAO Chen, XIA Yu, Adaptive fuzzy backstepping control for robot joint based on modified LuGre friction model [J], Journal of Hunan University(Natural Sciences), 49, 10, pp. 147-156, (2022)
  • [6] WANG S, Neural network-based adaptive funnel sliding mode control for servo mechanisms with friction compensation [J], Neurocomputing, 377, pp. 16-26, (2020)
  • [7] ZHOU Z, Adaptive sliding mode control of manipulators based on fuzzy random vector function links for friction compensation [J].Optik, 27, (2021)
  • [8] WANG Jun-xiao, YAN Xiao-dong, Jian-ming XU, Nonsingular fast terminal-sliding-mode control for flexible manipulator system based on disturbance and friction compensation [J], Control Theory & Application, 40, 7, pp. 1199-1207, (2023)
  • [9] LI Gang, Feng LI, DING Ruqi, Terminal force soft sensing of hydraulic manipulator based on joint torque compensation [J], Journal of South China University of Technology(Natural Science Edition), 50, 10, pp. 140-152, (2022)
  • [10] GENG Lingbo, CHEN Bai, WU Hongtao, Identification of articulated robots’dynamics parameters based on linkage-assemblies method [J], Chinese Journal of Mechanical Engineering, 25, 5, pp. 581-587, (2014)