Nonlinear friction dynamic modeling and performance analysis of flexible parallel robot

International Journal of Advanced Robotic Systems

article

Lei Zhao¹  Xin-hua Zhao¹  Bin Li¹  Yu-wei Yang¹  Liang Liu¹ 

[1] School of Mechanical Engineering, Tianjin University of Technology;Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology;National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology

关键词: Flexible parallel robot;    nonlinear friction;    dynamic modeling;    peak error;    stability;   

DOI  :  10.1177/1729881420972517

学科分类：社会科学、人文和艺术（综合）

来源: InTech

【 摘 要 】

The article presents a friction dynamic modeling method for a flexible parallel robot considering the characteristics of nonlinear friction. An approximate friction model which is proposed by Kostic et al. is applied to establish the dynamic model with Lagrange method. Parameters identification is completed by least square method, and the tracking accuracy and the stability of the robot are systematically analyzed before and after dynamic compensation at different speeds. Its position error of the robot after compensation is only 0.98 mm at low speed. The accuracy is improved 10 times than that before compensation. In addition, the peak velocity errors are 3.97 mms 1 and 1.49 mms 1 at high and low speed, respectively, which are reduced 2.5 times than that before compensation. The experimental data also indicate that velocity tracking curve has no obvious peak error compared with the common method based on Coulomb and viscous friction model. The curve is much smoother with proposed model, and the motion stability of robot at high speed has been greatly improved. The proposed method just needs the robot to collect some positions before path tracing, and the parameters identification of dynamic model can be completed quickly. The compensation effect is much more better than common method. So the proposed method can be extended to complete the dynamic identification for complex robot with more joints. It is helpful to further improve the stability and the accuracy at high speed. Ke

【 授权许可】

CC BY