Improved dynamic parameter identification method relying on proprioception for manipulators

2021 ◽  
Author(s):  
Jidong Jia ◽  
Minglu Zhang ◽  
Changle Li ◽  
Chunyan Gao ◽  
Xizhe Zang ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Dynamic Parameter ◽  
Identification Method ◽  
Dynamic Parameter Identification

scholarly journals A dynamic parameter identification method of industrial robots considering joint elasticity

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141882521 ◽  
Author(s):  
Hepeng Ni ◽  
Chengrui Zhang ◽  
Tianliang Hu ◽  
Teng Wang ◽  
Qizhi Chen ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Dynamic Model ◽  
Joint Stiffness ◽  
Dynamic Parameter ◽  
Industrial Robots ◽  
Identification Accuracy ◽  
Processing Algorithm ◽  
Identification Method ◽  
Joint Elasticity ◽  
Dynamic Parameter Identification

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.

A Dynamic Parameter Identification Method for Flexible Joints Based on Adaptive Control

2018 ◽  
Vol 23 (6) ◽  
pp. 2896-2908 ◽  
Author(s):  
Hongzhe Jin ◽  
Zhangxing Liu ◽  
Hui Zhang ◽  
Yubin Liu ◽  
Jie Zhao
Keyword(s):  
Adaptive Control ◽  
Parameter Identification ◽  
Dynamic Parameter ◽  
Flexible Joints ◽  
Identification Method ◽  
Dynamic Parameter Identification
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