Smooth Control of Rigid Flexible Coupling end Fitting for Industrial Robots under High Loads

In order to improve the smoothness of joint torque and end coupling ability of industrial robots under high loads, a rigid flexible coupling end fitting smoothness control method for industrial robots under high loads based on adaptive adjustment of joint torque is proposed. Construct a kinematic model of the joint drive unit for the kinematics and statics of industrial robots, and use the symmetrical structure combination arrangement method of the robot’s support frame to achieve joint adjustment of the flexible cable drive for the end position of the industrial robot. Decoupling variable stiffness control is carried out based on the static equilibrium conditions. Under high load conditions, the rigid flexible coupling end fitting of the robot is achieved through rapid motion conversion and adaptive adjustment of the high-speed motion end pose. Based on the joint parameter estimation of Coulomb friction force, viscous friction force, static friction force, and Stribeck model, smooth control of the rigid flexible coupling end fitting of the industrial robot is achieved. The simulation results show that using this method for controlling industrial robots under high loads can accurately achieve motion trajectory control of the robot. By pre measuring the changes in joint forces during motion, autonomous position identification of the robot can be achieved.

Authors

Institutions

Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.04.165
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smooth Control of Rigid Flexible Coupling end Fitting for Industrial Robots under High Loads

Jianqi Liu, Xinghua Lu, Zhijun Zhao, Bingzhi Zou
Procedia Computer Science
Robotic Mechanisms and Dynamics
article

Smooth Control of Rigid Flexible Coupling end Fitting for Industrial Robots under High Loads

Jianqi Liu, Xinghua Lu, Zhijun Zhao, Bingzhi Zou
article en

Abstract

In order to improve the smoothness of joint torque and end coupling ability of industrial robots under high loads, a rigid flexible coupling end fitting smoothness control method for industrial robots under high loads based on adaptive adjustment of joint torque is proposed. Construct a kinematic model of the joint drive unit for the kinematics and statics of industrial robots, and use the symmetrical structure combination arrangement method of the robot’s support frame to achieve joint adjustment of the flexible cable drive for the end position of the industrial robot. Decoupling variable stiffness control is carried out based on the static equilibrium conditions. Under high load conditions, the rigid flexible coupling end fitting of the robot is achieved through rapid motion conversion and adaptive adjustment of the high-speed motion end pose. Based on the joint parameter estimation of Coulomb friction force, viscous friction force, static friction force, and Stribeck model, smooth control of the rigid flexible coupling end fitting of the industrial robot is achieved. The simulation results show that using this method for controlling industrial robots under high loads can accurately achieve motion trajectory control of the robot. By pre measuring the changes in joint forces during motion, autonomous position identification of the robot can be achieved.

Procedia Computer ScienceVol. 261
Guangdong University Of Finances and Economics (CN)
Openalex Percentile: Top 88%
Robotic Mechanisms and Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.