A dynamic parameter identification method of industrial robots considering joint elasticity Article Swipe
YOU?
·
· 2019
· Open Access
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· DOI: https://doi.org/10.1177/1729881418825217
Considering the joint elasticity, a novel dynamic parameter identification method is proposed for general industrial robots only with motor encoders. Firstly, the unknown parameters of the elastic joint dynamic model are analyzed and divided into two types. The first type is the motion-independent parameter only including the joint stiffness, which can be identified by the static force/torque-deformation experiments without the dynamic model. The second type is the motion-dependent parameter composed of the rest of the parameters, which needs the dynamic excitation experiments. Therefore, these two types of parameters can be identified separately. Meanwhile, it is found that the rotor inertia parameters can be obtained from the manufacturer, which reduces the identification difficulty of other parameters. After obtaining the rotor inertia and joint stiffness, an approximate processing algorithm is proposed considering the motor friction to establish the linear identification model of other parameters. Hence, the least squares can be employed to identify the parameters, and the independence of the inertia and joint viscous friction parameters are not affected. Meanwhile, the exciting trajectories can be optimized throughout the robot workspace, which reduces the effect of measurement noise on identification accuracy. With the proposed separated identification strategy and approximate processing algorithm, the dynamic parameters can be obtained precisely without double encoders on each joint. Finally, a series of simulations are conducted to evaluate the good performance of the proposed method.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/1729881418825217
- https://journals.sagepub.com/doi/pdf/10.1177/1729881418825217
- OA Status
- gold
- Cited By
- 25
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2912383555
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2912383555Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1177/1729881418825217Digital Object Identifier
- Title
-
A dynamic parameter identification method of industrial robots considering joint elasticityWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-01Full publication date if available
- Authors
-
Hepeng Ni, Chengrui Zhang, Tianliang Hu, Teng Wang, Qizhi Chen, Chao ChenList of authors in order
- Landing page
-
https://doi.org/10.1177/1729881418825217Publisher landing page
- PDF URL
-
https://journals.sagepub.com/doi/pdf/10.1177/1729881418825217Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.sagepub.com/doi/pdf/10.1177/1729881418825217Direct OA link when available
- Concepts
-
Inertia, Computer science, Control theory (sociology), Joint stiffness, Stiffness, Encoder, Elasticity (physics), Torque, Robot, Rotor (electric), Workspace, Joint (building), Artificial intelligence, Structural engineering, Engineering, Physics, Thermodynamics, Control (management), Operating system, Classical mechanics, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
25Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 3, 2023: 4, 2022: 7, 2021: 1Per-year citation counts (last 5 years)
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26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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