A novel dynamic model parameters identification method for robotic manipulator based on the feasible physical constraints

The dynamic model of robots plays a crucial role in control tasks. The traditional Coulomb-viscous friction model inadequately describes friction torque, and the conventional identification strategy is ineffective in accurately identifying dynamic models with full physical parameters while meeting physically feasible constraints. In this paper, we propose a two-step strategy for identifying dynamic model parameters of manipulators based on nonlinear friction models. We establish the manipulator dynamic model using an improved Stribeck friction model. Firstly, the manipulator and friction force are separated, maintaining the nonlinear characteristics of the friction force while linearizing the manipulator. Secondly, the two components are optimized separately, incorporating physical feasibility constraints throughout the process. To evaluate the proposed method, a series of comparison experiments are conducted on the xMate Pro 3 manipulator plant. Experimental results demonstrate that the two-step identification strategy significantly improves identification accuracy. Meanwhile, the improved Stribeck friction model improves the comprehensive accuracy of parameter identification by 46%.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2026-09-29
DOI
https://doi.org/10.1177/09544062261481161
Primary Topic
Robot Manipulation and Learning
Type
article
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article

A novel dynamic model parameters identification method for robotic manipulator based on the feasible physical constraints

Tangzhong Song, Lijin Fang, Hanyu Pang, Yingcai Wan et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Robot Manipulation and Learning
article

A novel dynamic model parameters identification method for robotic manipulator based on the feasible physical constraints

Tangzhong Song, Lijin Fang, Hanyu Pang, Yingcai Wan, Li Li, Xinfeng Tang
article en

Abstract

The dynamic model of robots plays a crucial role in control tasks. The traditional Coulomb-viscous friction model inadequately describes friction torque, and the conventional identification strategy is ineffective in accurately identifying dynamic models with full physical parameters while meeting physically feasible constraints. In this paper, we propose a two-step strategy for identifying dynamic model parameters of manipulators based on nonlinear friction models. We establish the manipulator dynamic model using an improved Stribeck friction model. Firstly, the manipulator and friction force are separated, maintaining the nonlinear characteristics of the friction force while linearizing the manipulator. Secondly, the two components are optimized separately, incorporating physical feasibility constraints throughout the process. To evaluate the proposed method, a series of comparison experiments are conducted on the xMate Pro 3 manipulator plant. Experimental results demonstrate that the two-step identification strategy significantly improves identification accuracy. Meanwhile, the improved Stribeck friction model improves the comprehensive accuracy of parameter identification by 46%.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Liaoning Technical University (CN), Shanghai Jiao Tong University (CN), Northeastern University (CN)
Openalex Percentile: Top 16%
Robot Manipulation and Learning
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A novel dynamic model parameters identification method for robotic manipulator based on the feasible physical constraints — Tangzhong Song, Lijin Fang, et al. · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2026) | TGRS Research Map | TGRS