Error Theoretical Analysis of Robot Joint and Research on Parameter Identification Methods

doi:10.3901/JME.2025.17.015

Abstract

Abstract: The joints of robots often exhibit complex dynamic characteristics such as strong nonlinear stiffness and hysteresis, nonlinear friction, and kinematic transmission errors. These factors significantly impact the positioning accuracy and smoothness of joint movements. Therefore, analyzing joint errors and studying parameter identification methods are crucial. This research uses the PSO-LSSVM algorithm to obtain an accurate Preisach model for robot joints, describing their nonlinear stiffness and hysteresis characteristics. The FFT algorithm is employed to identify the high amplitude components in the kinematic transmission error model. The Levenberg-Marquardt algorithm is used to accurately obtain the Stribeck model, which describes the nonlinear friction characteristics of robot joints. Finally, based on the analysis results of the error models and identification algorithms, experiments were designed to verify the reliability of the models and identification methods. This research can provide references for the subsequent design of high-precision robot joint controllers.

Key words: robotic, joints, error model, parameter identification

CLC Number:

TP24

YAN Wenjun, CAI Yueri. Error Theoretical Analysis of Robot Joint and Research on Parameter Identification Methods[J]. Journal of Mechanical Engineering, 2025, 61(17): 15-26.

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