Nonlinear Joint Stiffness Parameter Identification

2021 ◽  
pp. 379-392
Author(s):  
Sanjay B. Ingole ◽  
Sanjay W. Rajurkar
Keyword(s):  
Parameter Identification ◽  
Joint Stiffness ◽  
Stiffness Parameter ◽  
Nonlinear Joint

The parameter identification model considering both geometric parameters and joint stiffness

2019 ◽  
Vol 47 (1) ◽  
pp. 76-81
Author(s):  
Jing Bai ◽  
Le Fan ◽  
Shuyang Zhang ◽  
Zengcui Wang ◽  
Xiansheng Qin
Keyword(s):  
Parameter Identification ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Geometric Parameters ◽  
Least Square ◽  
Experimental Result ◽  
Positional Accuracy ◽  
Content Type ◽  
The Absolute ◽  
Identification Model

Purpose Both geometric and non-geometric parameters have noticeable influence on the absolute positional accuracy of 6-dof articulated industrial robot. This paper aims to enhance it and improve the applicability in the field of flexible assembling processing and parts fabrication by developing a more practical parameter identification model. Design/methodology/approach The model is developed by considering both geometric parameters and joint stiffness; geometric parameters contain 27 parameters and the parallelism problem between axes 2 and 3 is involved by introducing a new parameter. The joint stiffness, as the non-geometric parameter considered in this paper, is considered by regarding the industrial robot as a rigid linkage and flexible joint model and adds six parameters. The model is formulated as the form of error via linearization. Findings The performance of the proposed model is validated by an experiment which is developed on KUKA KR500-3 robot. An experiment is implemented by measuring 20 positions in the work space of this robot, obtaining least-square solution of measured positions by the software MATLAB and comparing the result with the solution without considering joint stiffness. It illustrates that the identification model considering both joint stiffness and geometric parameters can modify the theoretical position of robots more accurately, where the error is within 0.5 mm in this case, and the volatility is also reduced. Originality/value A new parameter identification model is proposed and verified. According to the experimental result, the absolute positional accuracy can be remarkably enhanced and the stability of the results can be improved, which provide more accurate parameter identification for calibration and further application.

Parameter Identification of a Nonlinear Joint Within a Noise Path Synthesis Framework

2005 ◽  
Author(s):  
Todd Rook
Keyword(s):  
Parameter Identification ◽  
Joint Properties ◽  
Nonlinear Joint ◽  
Path Synthesis

An efficient noise path synthesis (NPS) approach which has been previously developed has been enhanced by coupling it with a parameter identification (PI) scheme to estimate effective joint properties.

Dimensionless Sensitivity Methods to Identify Vehicle Cornering Stiffness From Yaw Rate Measurements

2003 ◽  
Author(s):  
Sean N. Brennan
Keyword(s):  
Network Analysis ◽  
Parameter Identification ◽  
System Model ◽  
Model Description ◽  
Stiffness Parameter ◽  
Yaw Rate ◽  
Bicycle Model ◽  
Experimental Implementation ◽  
Simplified Method ◽  
Vehicle Chassis

A simplified method of identifying a dynamic model is presented that utilizes explicit and implicit coupling between Bode parameter sensitivities. This focus of this work is the identification, in real-time, of the Cornering Stiffness parameter. This parameter governs the tire-road interaction within the simplified bicycle model description of vehicle chassis dynamics at highway speeds. This novel sensitivity coupling method, discovered earlier as sensitivity invariance in circuit network analysis, explicitly limits the possible parameter gradients of the system model to a very small subspace. By constraining the parameter identification or adaptation to solely this possible subspace, a simplified and efficient parameter identification can be obtained at a reduced computational and modelling cost. Both simulation and experimental implementation on a research vehicle under changing road conditions are presented.

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.

Method of Bending Stiffness Parameter Identification of Stay Cable

2015 ◽  
Vol 777 ◽  
pp. 52-58
Author(s):  
Hong Du ◽  
Da Yang Liu ◽  
Fu Wei Huang ◽  
Jing Bo Liao
Keyword(s):  
Parameter Identification ◽  
Bending Stiffness ◽  
Parameters Identification ◽  
Stiffness Ratio ◽  
Stiffness Parameter ◽  
Stay Cable ◽  
Cable Tension ◽  
Cable Length

In order to solve the problem of bending stiffness parameters identification of practical stay-cable, and provide bending stiffness correction for tension measurement. A method to identify cable bending stiffness parameters is proposed, and its basis theory established in paper. The method was applied to Xiazhang Sea-Crossing Bridge, the results showed that: Identification bending stiffness ratio is between 0.33 to 0.54 for relatively short cables of South Branch Bridge, and it tends to decrease with increase of cable length and force. However, the identification bending stiffness is close or equal to 0 EImax for relatively long cable of North Branch Bridge. It testified that the effect of bending stiffness for long cable tension is small in engineering.

scholarly journals On Stability of Virtual Torsion Sensor for Control of Flexible Robotic Joints with Hysteresis

Robotica ◽  
2019 ◽  
Vol 38 (7) ◽  
pp. 1191-1204 ◽  
Author(s):  
Michael Ruderman
Keyword(s):  
Position Control ◽  
Joint Stiffness ◽  
Control Loop ◽  
Positioning Control ◽  
Robotic Joints ◽  
Error Dynamics ◽  
The Stability ◽  
Hardware Costs ◽  
Joint Load ◽  
Nonlinear Joint

SUMMARYThe aim of the virtual torsion sensor (VTS) is to observe the nonlinear deflection in the flexible joints of robotic manipulators and, by its use, improve positioning control of the joint load. This model-based approach utilizes the motor-side sensing only and, therefore, replaces the load-side encoders at nearly zero hardware costs. For being applied in the closed control loop, the stability and robustness of VTS are most crucial. This work extends the previous analysis by a general case of nonlinear joint stiffness with hysteresis and provides straightforward conditions with respect to the system dynamics. The dissipativity and passivity of the torsion-torque hysteresis map are analyzed and discussed in detail. The absolute stability of VTS inclusion into position control loop is shown based on the equivalent loop transformations and Popov criteria, including the sector conditions. Illustrative numerical examples of the control error dynamics and its convergence are provided.

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