Friction parameters identification and compensation of LuGre model base on genetic algorithms

Yan, Wen; Chu, M. S.; Sun, Hanxu

doi:10.2991/isci-15.2015.33

Cited by 6 publications

(5 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To test the dynamic response characteristics of the constant force tracking and the effectiveness of the friction observer, the expected force for approximately 0-1 s is set to 8 N and that of approximately 1-2 s is 12 N. It can be seen from Figure 8 that the response time of proportion integration differentiation (PID), integral sliding mode controller (ISMC), extended state observer-based active disturbance rejection controller (ESO 1 ADRC) and ALuGre 1 Backstepping controllers is 260 ms, 255 ms, 170 ms and 80 ms, The actual friction force of the cylinder in the step force response process is simulated according to equations ( 10) and ( 11). The parameters of friction in equation ( 10), s 0 and s 1 , are chosen to be 95 N/m and 0.006 N s/m (Wen et al, 2015). It can be seen from Figure 9 that the friction force observer has a good estimation of actual friction force.…”

Section: Step Force Tracking Response Simulationmentioning

confidence: 99%

“…The actual friction force of the cylinder in the step force response process is simulated according to equations (10) and (11). The parameters of friction in equation (10), σ 0 and σ 1 , are chosen to be 95 N/m and 0.006 N • s/m (Wen et al , 2015). It can be seen from Figure 9 that the friction force observer has a good estimation of actual friction force.…”

Section: Simulation Analysismentioning

confidence: 99%

“…The LuGre friction model proposed in Wit et al (1995) can accurately describe various dynamic and static characteristics of friction, so it is widely used. As the traditional LuGre model is piecewise continuous, some scholars adopt intelligent control methods such as genetic algorithm (Wen et al , 2015) and neural network (Quaranta et al , 2020) to deal with problems in LuGre model. However, these methods are difficult to be applied to engineering practice because of the large amount of calculation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive friction compensation control of robotic pneumatic end-effector based on LuGre model

Dai

et al. 2023

View full text Add to dashboard Cite

Purpose Considering the response lag and viscous slip oscillation of the system caused by cylinder piston friction during automatic polishing of aero-engine blades by a robotic pneumatic end-effector, the purpose of this study is to propose a constant force control method with adaptive friction compensation. Design/methodology/approach First, the mathematical model of the pneumatic end-effector is established based on the continuous LuGre model, and the static parameters of the LuGre model are identified to verify the necessity of friction compensation. Second, aiming at the problems of difficult identification of dynamic parameters and unmeasurable internal states in the LuGre model, the parameter adaptive law and friction state observer are designed to estimate these parameters online. Finally, an adaptive friction compensation backstepping controller is designed to improve the response speed and polishing force control accuracy of the system. Findings Simulation and experimental results show that, compared with proportion integration differentiation, extended state observer-based active disturbance rejection controller and integral sliding mode controller, the proposed method can quickly and effectively suppress the polishing force fluctuation caused by nonlinear friction and significantly improve the blade quality. Originality/value The pneumatic force control method combining backstepping control with the friction adaptive compensation based on LuGre friction model is studied, which effectively suppresses the fluctuation of normal polishing force.

show abstract

Section: Step Force Tracking Response Simulationmentioning

confidence: 99%

Section: Simulation Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive friction compensation control of robotic pneumatic end-effector based on LuGre model

Dai

et al. 2023

View full text Add to dashboard Cite

show abstract

“…There are six required parameters: bristle stiffness, bristle damping coefficient, viscous damping coefficient, Coulomb friction level, static friction level, and Stribeck velocity. The LuGre model is divided into static analysis and dynamic analysis, and parameters are obtained through experiments [17,18]. Motor current is measured as rotational speed ω is controlled.…”

Section: Friction Compensationmentioning

confidence: 99%

Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism

Zhang

Jeong

Kim

et al. 2021

Sensors

View full text Add to dashboard Cite

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and handle surgical instruments. It also presents a force-free control algorithm for the direct teaching of end effectors. The bidirectional telescopic mechanism can actively transmit force both upwards and downwards by staggering the wires on both sides. In order to estimate and control torque via motor current without a force/torque sensor, the gravity model and friction model of the device are derived through repeated experiments. The LuGre model is applied to the friction model, and the static and dynamic parameters are obtained using a curve fitting function and a genetic algorithm. Direct teaching control is designed using a force-free control algorithm that compensates for the estimated torque from the motor current for gravity and friction, and then converts it into a position control input. Direct teaching operation sensitivity is verified through hand-guiding experiments.

show abstract

“…Because the LuGre friction model is highly nonlinear and has first-order differential terms, it is easy to fall into the local optimal problem during the process of the model parameter identification by genetic algorithm [ 36 ]. In response to the above, different initial rounds of evolutionary optimization initial parent populations were set up to solve the local optimal problem of parameter identification for highly nonlinear differential LuGre friction model.…”

Section: Friction Modeling and Parameter Identificationmentioning

confidence: 99%

Disturbance Recognition and Collision Detection of Manipulator Based on Momentum Observer

Zhang

Zhao

Zhang

et al. 2020

Sensors

View full text Add to dashboard Cite

Increasing requirements for the safety of human-robot interaction and the cost-effectiveness of collision detection rapidly promote the development of collision detection technology without torque sensors. To address nonlinear disturbance factors in collision detection that may cause unstable or even incorrect detection, this paper proposed a research strategy that considered the friction as the disturbance term in manipulator motion for the collision detection. The manipulator joint disturbance model was established based on the LuGre dynamic friction model, and the external torque observer was designed based on the generalized momentum. Then, the friction measurement was realized using the external torque observer, and the model parameters were identified through the genetic algorithm. The collision detection can be reduced errors after the friction model by compensating the disturbance and can be applicable to variable working conditions. Finally, the accuracy of the constructed disturbance model and the performance of the proposed collision detection method were validated by the experimental studies.

show abstract

Friction parameters identification and compensation of LuGre model base on genetic algorithms

Cited by 6 publications

References 4 publications

Adaptive friction compensation control of robotic pneumatic end-effector based on LuGre model

Adaptive friction compensation control of robotic pneumatic end-effector based on LuGre model

Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism

Disturbance Recognition and Collision Detection of Manipulator Based on Momentum Observer

Contact Info

Product

Resources

About