• Title/Summary/Keyword: LuGre model

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Vibration Simulation Using LuGre Friction Model for Cladding Tube Fretting Wear Analysis (피복관 프레팅마모 해석을 위한 LuGre 마찰모델 성능 고찰)

  • Park, Nam-Gyu;Kim, Jin-Seon;Kim, Joong-Jin;Kim, Jae-Ik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.26 no.1
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    • pp.55-62
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    • 2016
  • Nuclear fuels are always exposed to hot temperature and high speed coolant flow during the reactor operation. Thus the fuel rod accompanies small amplitude vibration due to the turbulent flow. The random vibration causes friction between the fuel rod and the grid structure which provides the lateral supports. The friction is critical to the fuel rod fretting wear, and it degrades fuel performance when a severe wear is developed. LuGre friction model is introduced in the paper, and the performance was evaluated comparing to the classical Coulomb model. It is shown that the developed friction force considering the Coulomb friction is not enough to stop or delay the motion while the stick-slip can be simulated using LuGre friction model. Numerical solutions of the two dimensional spacer grid cell model with the modern friction are also reviewed, and it is discussed that the new friction model simulates well the nonlinear mechanism.

Position Control of Servo Systems Using Feed-Forward Friction Compensation (피드포워드 마찰 보상을 이용한 서보 시스템의 위치 제어)

  • Park, Min-Gyu;Kim, Han-Me;Shin, Jong-Min;Kim, Jong-Shik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.5
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    • pp.508-513
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    • 2009
  • Friction is an important factor for precise position tracking control of servo systems. Servo systems with highly nonlinear friction are sensitive to the variation of operating condition. To overcome this problem, we use the LuGre friction model which can consider dynamic characteristics of friction. The LuGre friction model is used as a feed-forward compensator to improve tracking performance of servo systems. The parameters of the LuGre friction model are identified through experiments. The experimental result shows that the tracking performance of servo systems with higherly nonlinear friction can be improved by using feed-forward friction compensation.

Position Control for the XY Drive System with Lu-Gre Friction Model (Lu-Gre 마찰 모델을 갖는 XY구동계의 위치제어)

  • 한성익;방두열
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.186-189
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    • 2001
  • In a precise control system, the Lu-Gre friction model has often been used to describe the nonlinear friction. For the XY table system with this friction model, we identified the friction parameters and designed nonlinear observer. The nonlinear friction effects could be removed within appropriate position tracking errors and control inputs through experiments. Also, we designed the nonmodel-based SMC system to compensate the nonlinear friction. Through experiments, it is shown that this method has the similar performance compared with the nonlinear observer system and is useful when friction parameters are hard to identify except the problem of input chattering.

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Modelling and Development of Control Algorithm of Endoscopy

  • Ma, Weichao;Lee, Sanghyuk
    • Journal of Convergence Society for SMB
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    • v.4 no.2
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    • pp.33-39
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    • 2014
  • In this paper, basic backgrounds about capsule endoscopy are introduced, and the aims and objectives are also illustrated. Methodology and mathematical model for LuGre model were investigated to analyse system characteristics. A nonlinear friction model, the stick-slip motion system based on LuGre friction model was used to simulate the motion of capsule endoscopy inside human body. Under the different situation, LuGre friction model was simulated by Matlab Simulink software. The entire cycle of motion and the influence of parameters towards to velocity are fully simulated.

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LuGre Model-Based Neural Network Friction Compensator in a Linear Motor Stage

  • Horng, Rong-Hwang;Lin, Li-Ren;Lee, An-Chen
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.2
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    • pp.18-24
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    • 2006
  • This paper proposes a LuGre Model-Based Neural Network (MBNN) friction compensation algorithm for a linear motor stage. For matching the friction phenomena in both the motion-start region and the motion-reverse region, the LuGre dynamic model is employed into the proposed compensation algorithm. After training of the model-based neural network is completed, the estimated friction for compensation is obtained. From the obtained result we find that the new structure gains advantage over the non-friction compensation system on the performance of the compensator in both regions. The proposed compensator is evaluated and compared experimentally with an uncompensated system on a microcomputer controlled linear motor tracking system in the final section of the paper. The experimental results show the improvement on the maximum velocity error and the root mean square tracking error in the motion-start region ranges from 34% to 53% and from 53% to 75% respectively, and in the motion-reverse region from 48% to 65% and from 79% to 90% respectively.

Friction Compensation of the Pendubot based on the LuGre Model (LuGre 모델에 기반한 펜듀봇의 마찰력 보상)

  • Eom, Myung-Whan;Kim, Cheol-Joong;Chwa, Dong-Kyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.4
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    • pp.848-855
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    • 2011
  • This paper proposes a method to reduce the limit cycle phenomenon that appears in the steady-state response of a pendubot system, when it is controlled by a state feedback controller based on the linearized system model. For this, we employed the compensator which estimates the friction based on the LuGre model in the LQR control. The proposed compensation method is validated by experiments for a pendubot system, which shows that the external disturbance as well can be efficiently compensated.

Robust Position Control for PMLSM Using Friction Parameter Observer and Adaptive Recurrent Fuzzy Neural Network (마찰변수 관측기와 적응순환형 퍼지신경망을 이용한 PMLSM의 강인한 위치제어)

  • Han, Seong-Ik;Rye, Dae-Yeon;Kim, Sae-Han;Lee, Kwon-Soon
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.2
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    • pp.241-250
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    • 2010
  • A recurrent adaptive model-free intelligent control with a friction estimation law is proposed to enhance the positioning performance of the mover in PMLSM system. For the PMLSM with nonlinear friction and uncertainty, an adaptive recurrent fuzzy neural network(ARFNN) and compensated control law in $H_{\infty}$ performance criterion are designed to mimic a perfect control law and compensate the approximated error between ideal controller and ARFNN. Combined with friction observer to estimate nonlinear friction parameters of the LuGre model, on-line adaptive laws of the controller and observer are derived based on the Lyapunov stability criterion. To analyze the effectiveness our control scheme, some simulations for the PMLSM with nonlinear friction and uncertainty were executed.

Development of a New Inchworm Actuation System U sing Piezoelectric Shearing Actuators (전단압전가진기를 이용한 인치웜 가진시스템의 개발)

  • Lee, Sang-Won
    • Journal of the Korean Society for Precision Engineering
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    • v.24 no.8 s.197
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    • pp.81-88
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    • 2007
  • This paper presents the development of a new inchworm actuation system using the shearing deformation of the piezoelectric actuators. In this new actuation system, piezoelectric shearing/expanding actuators, an inertial mass and an advanced preload system are configured innovatively to generate the motion of an inertial mass. There are two modes in the new actuation system: (1) stick mode, and (2) clamp mode. In stick mode, the deformation of the piezoelectric shearing actuators drives an inertial mass by means of the friction force at their contact interface. On the other hand, in clamp mode, the piezoelectric expanding actuators provide the gripping force to an inertial mass and, as a result, eliminate its backward motion following the rapid backward deformation of the piezoelectric shearing actuators. To investigate the feasibility of the proposed new actuation system, the experimental system is built up, and the static performance evaluation and dynamic analysis are conducted. The open-loop performance of the linear motion of the proposed new actuation system is evaluated. In dynamic analysis, the mathematical model for the contact interface is established based on the LuGre friction model and the equivalent parameters are identified.

Nonlinear Friction Control Using the Robust Friction State Observer and Recurrent Fuzzy Neural Network Estimator (강인한 마찰 상태 관측기와 순환형 퍼지신경망 관측기를 이용한 비선형 마찰제어)

  • Han, Seong-Ik
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.1
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    • pp.90-102
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    • 2009
  • In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.