• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1966-1971
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• 2005

Though several previous anti-windup techniques have been proposed, they are limited to linear systems or friction is not considered. Thus this paper proposes a compensation scheme for input-constrained robot systems with friction to cope with the windup phenomenon and shows its effectiveness by simulations. Given a feedback linearizing controller for a robot system designed without considering its input constraint, an additional dynamic compensator is proposed to account for the constraint. The dynamic anti-windup is based on the minimization of a reasonable performance index, and properties of the resulting closed-loop are presented.

• 한국생산제조학회지
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• 제7권4호
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• pp.130-135
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• 1998

This paper deals with a position control problem of a hydraulic proportional position control system using a friction compensation control. There are many nonlinearities in hydraulic systems. With only proportional controller, response is slow and steady-state error cannot be compensated properly. Controller designed in this paper achieves fast transient response through the velocity and acceleration feedback and good steady-state response through the friction compensator. A/D and D/A board is employed for data acquisition and manipulation. The experimental results are compared with computer simulation results using Matlab.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1828-1831
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• 2003

There are various sources causing a position error in a linear motor. This paper focuses on error sources from rotational motions of a table and friction. Rotational errors occur due to imperfections during manufacturing and/or assembly of guide ways, and cause a position error at locations of interest. Friction is another factor deteriorating the position error due to its highly nonlinear behavior. The position error of the linear motor was about 20∼30$\mu\textrm{m}$. After compensating the position errors due to rotational error motions and friction. the remaining errors become about 6～8$\mu\textrm{m}$ and 2～3$\mu\textrm{m}$, respectively. It is shown that the positional accuracy of a linear can be greatly improved by compensating the two error sources.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.426-428
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• 1998

In this paper, a ramp tracking controller design method is proposed for the systems with nonlinear frictions. The objective is to design a controller which is capable of tracking a ramp reference input without steady state error. The controller is composed of a linear controller, integrators for error compensation, and a friction compensator. The compensator estimates the parameters of friction model. The friction parameters are estimated using two different method. Simulation and experimental results show that the proposed method is effective.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.596-599
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• 2000

A natural admittance control system design is presented for a particular type of interaction controller that achieve high-performance and guarantees stability. The admittance control Significantly improves performance when Coulomb friction is present in the one link robot system. The technique requires a careful choice of the target impedance. Experimental performance results are presented for a two-mass system with internal Coulomb friction. Results demonstrate that the admittance control law is successful in rejecting internal Coulomb friction force disturbances. The controller was designed and implemented on our system that we set up one link robot system and hardware configuration system, and performance results are presented.

• 한국산학기술학회논문지
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• 제12권11호
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• pp.5194-5201
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• 2011

본 논문에서는 부분적으로 알고 있는 비선형 마찰력이 있는 2차 기계시스템에 대한 강인한 적응제어 기법을 제시한다. 제시하는 적응제어 방법은 잡음이나 모델링 에러가 없는 경우에는 위치 및 속도 추적 오차는 점근적으로 영으로 수렴함을 보장하며, 잡음이나 모델링 에러가 있는 경우에는 그동안 발표된 다른 논문의 결과와 달리 디자인 변수를 적절하게 선택하면 위치 및 속도 추적 오차를 원하는 범위까지 줄일 수 있음을 보였으며 이는 시뮬레이션 결과를 통해 입증하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.538-541
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• 1995

Joint flexibilities and frictional uncertainties are known to be a major cause of performance degration in motion control systems. This paper investigates the modeling and compensation of these undesired effects. A hybrid controller, which consists of a predictive controller and a neural network controller, is designed to overcome these undesired effects. Also learning scheme for friction uncertainies, which don't interfere with feedback controller dynamics, is discussed. Through simulation works with two inetia-torsional spring system having Coulomb friction, the effectiveness of the proposed hybrid controller was tested. The proposed predictive & neural network hybrid controller shows better performance over one when only predictive controller used.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.248-255
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• 2000

Whereas the linear PID controller is widely used for control of industrial servo systems a high precision positioning system is not easy to control only with the PID controller due to uncertain nonlinear dynamics such as friction backlash etc. As a viable means to overcome the difficulty a learning control scheme is proposed in this paper that is simple and straightforward to implement. The proposed learning controller takes full advantage of current feedback capability of the inner-loop of the control system in that electrical motor dynamics as the well as mechanical part of X-Y positioning system is included in the learning control scheme, The experimental results are given to demonstrate its feasibility and effectiveness in terms of convergence precision of tracking and robustness in comparison with the conventional control method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.70-70
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• 2000

Recently, a neuro-fuzzy approach, a combination of neural networks and fuzzy reasoning, has been playing an important role in the motor control. In this paper, a novel method of fiction compensation using neuro-fuzzy architecture has been shown to significantly improve the performance of a DC motor system with nonlinear friction characteristics. The structure of the controller is the neuro-fuzzy network with the TS(Takagi-Sugeno) model. A back-propagation neural network based on a gradient descent algorithm is employed, and all of its parameters can be on-line trained. The performance of the proposed controller is compared with both a conventional neuro-controller and a PI controller.

• 한국생산제조학회지
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• 제26권1호
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• pp.89-99
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• 2017

This paper describes the development of a thigh wearable robot for power assistance during stair climbing. In the wearable robot developed in this study, high-power BLDC motors and high-capacity harmonic reduction gears are used to effectively assist the thigh muscle during stair climbing. In particular, normal ground and stair are distinguished accurately by using wireless smart shoes, and the stair climbing assistance is performed by activating the actuators at an appropriate time. Impedance of the hip joint was effectively reduced by performing friction compensation of the gears, and a wearing adjustment mechanism was designed to fit the robot to the thigh by conveniently modifying the width and tilting angle of the robot using set collars. Consequently, the performance of the developed thigh wearable robot was verified through stair climbing experiments with EMG measurement.