scholarly journals Modelling the temperature in joint friction of industrial manipulators

Robotica ◽  
2017 ◽  
Vol 37 (5) ◽  
pp. 906-927 ◽  
Author(s):  
Luca Simoni ◽  
Manuel Beschi ◽  
Giovanni Legnani ◽  
Antonio Visioli
Keyword(s):  
Parameter Estimation ◽  
Temperature Sensor ◽  
Industrial Robot ◽  
Friction Torque ◽  
Dynamic Friction ◽  
New Model ◽  
Joint Friction ◽  
Experimental Campaign ◽  
Industrial Manipulators ◽  
Simplifying Assumptions

SummaryIn this paper, a new model for joint dynamic friction of industrial robot manipulators is presented. In particular, the effects of the temperature in the joints are considered. A polynomial-based model is proposed and the parameter estimation is performed without the need of a joint temperature sensor. The use of an observer is then proposed to compensate for the uncertainty in the initial estimation of the temperature value. A large experimental campaign show that the model, in spite of the simplifying assumptions made, is effective in estimating the joint temperature and therefore the friction torque during the robot operations, even for values of velocities that have not been previously employed.

scholarly journals A new joint friction model for parameter identification and sensor-less hand guiding in industrial robots

2020 ◽  
Vol 47 (6) ◽  
pp. 847-857
Author(s):  
Guanghui Liu ◽  
Qiang Li ◽  
Lijin Fang ◽  
Bing Han ◽  
Hualiang Zhang
Keyword(s):  
Industrial Robot ◽  
Angular Displacement ◽  
Weighted Least Squares ◽  
Friction Model ◽  
Industrial Robots ◽  
Model Parameters ◽  
Dynamic Parameters ◽  
Content Type ◽  
Joint Friction ◽  
Six Dof

Purpose The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction. The identification and sensor-less control algorithm are investigated to verify the validity of this model. Design/methodology/approach The proposed friction model is nonlinear and it considers the angular displacement and angular velocity of the joint as a secondary compensation for identification. In the present study, the authors design a pipeline – including a manually designed excitation trajectory, a weighted least squares algorithm for identifying the dynamic parameters and a hand guiding controller for the arm’s direct teaching. Findings Compared with the conventional joint friction model, the proposed method can effectively predict friction factors during the dynamic motion of the arm. Then friction parameters are quantitatively obtained and compared with the proposed friction model and the conventional friction model indirectly. It is found that the average root mean square error of predicted six joints in the proposed method decreases by more than 54%. The arm’s force control with the full torque using the estimated dynamic parameters is qualitatively studied. It is concluded that a light-weight industrial robot can be dragged smoothly by the hand guiding. Practical implications In the present study, a systematic pipeline is proposed for identifying and controlling an industrial arm. The whole procedure has been verified in a commercial six DOF industrial arm. Based on the conducted experiment, it is found that the proposed approach is more accurate in comparison with conventional methods. A hand-guiding demo also illustrates that the proposed approach can provide the industrial arm with the full torque compensation. This essential functionality is widely required in many industrial arms such as kinaesthetic teaching. Originality/value First, a new friction model is proposed. Based on this model, identifying the dynamic parameter is carried out to obtain a set of model parameters of an industrial arm. Finally, a smooth hand guiding control is demonstrated based on the proposed dynamic model.

scholarly journals A new model for predicting the mechanical efficiency of ball screws based on the empirical equations for the friction torque of rolling bearings

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401880017 ◽  
Author(s):  
Chang-Guang Zhou ◽  
Hu-Tian Feng ◽  
Yi Ou
Keyword(s):  
Rotational Speed ◽  
Axial Load ◽  
High Speed ◽  
Mechanical Efficiency ◽  
Friction Torque ◽  
Numerical Control ◽  
Measuring System ◽  
Empirical Equations ◽  
Rolling Bearings ◽  
New Model

Based on the empirical equations for the friction torque of rolling bearings, this article proposes a new model for predicting the friction torque and mechanical efficiency of ball screws. Meanwhile, a novel measuring system is constructed to obtain the mechanical efficiency of ball screws, where both the axial load and rotational speed are stable and adjustable. The experimental results at a rotational speed of 1000 r/min agree well with the theoretical values calculated by the present method, which show that the mechanical efficiency of ball screws increases with increasing axial load. Moreover, the model built in this article is more applicable to a relatively high-speed condition. The new model can be easily used to obtain the friction torque and mechanical efficiency for ball screws, which is essential for improving the performance of ball screws and the computer numerical control machine tools.

Modelling and Identification of a Six Axes Industrial Robot

2005 ◽  
Author(s):  
Rob Waiboer ◽  
Ronald Aarts ◽  
Ben Jonker
Keyword(s):  
Least Squares ◽  
Industrial Robot ◽  
Equations Of Motion ◽  
Experimental Parameter ◽  
Friction Model ◽  
Unknown Parameters ◽  
Joint Friction ◽  
Inertia Parameters ◽  
Value Decomposition ◽  
Least Squares Techniques

This paper deals with the modelling and identification of a six axes industrial Sta¨ubli RX90 robot. A non-linear finite element method is used to generate the dynamic equations of motion in a form suitable for both simulation and identification. The latter requires that the equations of motion are linear in the inertia parameters. Joint friction is described by a friction model that describes the friction behaviour in the full velocity range necessary for identification. Experimental parameter identification by means of linear least squares techniques showed to be very suited for identification of the unknown parameters, provided that the problem is properly scaled and that the influence of disturbances is sufficiently analysed and managed. An analysis of the least squares problem by means of a singular value decomposition is preferred as it not only solves the problem of rank deficiency, but it also can correctly deal with measurement noise and unmodelled dynamics.

scholarly journals Dynamic Model Identification for 6-DOF Industrial Robots

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Li Ding ◽  
Hongtao Wu ◽  
Yu Yao ◽  
Yuxuan Yang
Keyword(s):  
Robot Manipulator ◽  
Industrial Robot ◽  
Model Identification ◽  
Friction Model ◽  
Industrial Robots ◽  
Parameters Identification ◽  
Identification Algorithm ◽  
Unknown Parameters ◽  
Joint Friction ◽  
Dynamical Parameters

A complete and systematic procedure for the dynamical parameters identification of industrial robot manipulator is presented. The system model of robot including joint friction model is linear with respect to the dynamical parameters. Identification experiments are carried out for a 6-degree-of-freedom (DOF) ER-16 robot. Relevant data is sampled while the robot is tracking optimal trajectories that excite the system. The artificial bee colony algorithm is introduced to estimate the unknown parameters. And we validate the dynamical model according to torque prediction accuracy. All the results are presented to demonstrate the efficiency of our proposed identification algorithm and the accuracy of the identified robot model.

A Semiparametric Model-Based Friction Compensation Method for Multi-Joint Industrial Robot

2021 ◽  
Author(s):  
Miao He ◽  
Xiaomin Wu ◽  
Guifang Shao ◽  
Yuhua Wen ◽  
Tundong Liu
Keyword(s):  
Industrial Robot ◽  
Lyapunov Theory ◽  
Industrial Robots ◽  
Learning Ability ◽  
Robot System ◽  
Joint Friction ◽  
Tracking Tasks ◽  
Physical Information ◽  
The Stability ◽  
Six Degree Of Freedom

Abstract Industrial robots have received enormous attention due to their widespread uses in modern manufacturing. However, due to the frictional discontinuous and other unknown dynamics in robotic system, existing researches are limited to simulation and single- or double-joint robot. In this paper, we introduce a semiparametric controller combined by a radial basis function neural network (RBFNN) and complete physical model considering joint friction. First, to extend the NN controller to real-world problems, the continuously differentiable friction (CDF) model is adopted to bring physical information into the learning process. Then, RBFNN is employed to approximate the model error and other unmolded dynamics, and the parameters of CDF model are updated online according to its learning ability. The stability of the robot system can be guaranteed by the Lyapunov theory. The primary parameters of CDF model are determined by the identification experiment and subsequently iteratively updated by the NN. Real-time tracking tasks are performed on a six degree of freedom (DoF) manipulator to follow the desired trajectory. Experimental results demonstrate the effectiveness and superiority of the proposed controller, especially at low speed.

Static Analysis of Spherical nR Kinematic Chains With Joint Friction

1992 ◽  
Author(s):  
Pierre Larochelle ◽  
J. M. McCarthy
Keyword(s):  
Static Analysis ◽  
Bending Moment ◽  
Iterative Solution ◽  
Friction Model ◽  
Friction Torque ◽  
Force Balance ◽  
External Loading ◽  
Linear System Of Equations ◽  
Kinematic Chains ◽  
Joint Friction

Abstract This paper presents the static analysis of general spherical nR simple open or closed kinematic chains with joint friction. The internal loading on each link is found to consist of a bending moment and a torsional moment. The goal of this analysis is to determine these moments which are then used in designing the link. The moment and force balance equations for each link yields a linear system of equations which define the internal moments of the mechanism and the output torque on the driven crank for a given input torque. A Coulomb model of joint friction is used to determine the friction torque along the axis of a joint. The joint friction model requires an iterative solution. The purpose of this algorithm is to provide a means of computing the complete internal and external loading on the members of spherical chains while including frictional effects in order to facilitate the design of a functional spherical mechanisms.

The Closed-Form Equation of Motion of a Human Body With Joint Friction

2013 ◽  
Author(s):  
Qingmin Huang ◽  
Ye-Hwa Chen ◽  
Xin Nie
Keyword(s):  
Closed Form ◽  
Human Body ◽  
Free Fall ◽  
Analytic Form ◽  
Equation Of Motion ◽  
Friction Torque ◽  
Constraint Forces ◽  
Constraint Force ◽  
Joint Friction ◽  
And Control

A general method for equation of motion of a human body is presented. The equation is in closed-form (i.e., analytic form). A hierarchical approach is introduced to get the equation of motion of the human body. The constraint force between subsystems is explicitly obtained which can be used to calculate the joint friction torque. The final equation of motion includes the dynamics of the unconstrained motion, the constraints, and the constraint forces including the joint friction torque induced by the nonideal constraints. No auxiliary variables such as Lagrange multipliers or pseudo-generalized speeds are needed. Therefore the equation of motion is most suitable for generic dynamic analysis and control design. A four-segment, planar, articulated linkage free fall human body is chosen to demonstrate this method.

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