• 항공우주시스템공학회지
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• 제9권4호
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• pp.23-30
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• 2015

The focal plane image stabilization for a camera is one of the most effective method that can increases the digital camera's image quality by compensating the vibration disturbance. The optical image stabilization can be implemented by making the focal plane to trace the path of incident light. To control the position of focal plane motion compensating stage precisely, a nonlinear control algorithm has been applied by considering coulomb friction which is nonlinear behavior of the compensator system. In our study, we have analyzed the hand shaking vibration using the gyro sensor, and made a mathematical model of compensating stage containing optical sensor and piezo-actuator. Then the nonlinear control algorithm has been designed and its performance has been verified by experiment. In this study, a friction driven peizo-electric actuator with $1{\mu}m$ resolution and 10mm/s speed has been used for stage movement.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.111-116
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• 2001

A neural network compensator for stick-slip friction phenomena in meashartonics servo systems is practically proposed to supplement the traditionally available position and velocity control loops for precise motion control. The neural network compensa-tor plays the role of canceling the effect of nonlinear slipping friction force. It works robustly and effectively in a real control system. This enables the mechatronics servo systems to provide more precise control in the digital computer. It was confirmed that the con-trol accuracy is improved near zero velocity and points of changing the moving direction through numerical simulation. However, asymptotic property on the steady state error of the normal operation points is guaranteed by the integral term of traditional velocity loop controller.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.179-179
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• 2000

An adaptive neural network compensator for stick-slip friction phenomena in servo systems is proposed to supplement the traditionally available position and velocity control loops for precise motion control. The neural network compensator plays a role of canceling the effect of nonlinear slipping friction force. This enables the mechatronic systems more precise control and realistic design in the digital computer. It was confirmed that the control accuracy is more improved near zero velocity and the points of changing the moving direction through numerical simulation

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.893-898
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• 2003

Coulomb friction is an important factor for precise position tracking control systems. The control systems with friction causes the steady state error because of being sensitive to the change of system condition and highly nonlinear characteristics. To overcome these problems, we use an estimation scheme of Coulomb friction to experiment for it's compensating. The estimated factor for Coulomb friction is used as a feed-forward compensator to improve the tracking performance of ball-screw systems. The tracking performance was improved by compensating the estimated friction torque in the feed-forward term. And, the sliding mode control which is derived from the Lyapunov stability theorem is applied for robust stability and reducing chattering. The experimental results show that the sliding mode controller with adaptive friction compensator has a good tracking performance compared with the friction uncompensated controller.

• 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.

• 전기학회논문지P
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• 제59권2호
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.524-527
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• 1988

Basic types of bilateral servo systems were described and practical consideration in the bilateral servo controller design was introduced. Power assistance to the operator is essential for high efficiency and accurate force reflection is necessary for dexterous manipulation. This paper shows a controller structure under development at KIMM which employs nonlinear friction compensation and memory based gravity compensation technique for efficiency and dexterity.

• 한국정밀공학회지
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• 제21권2호
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• pp.35-42
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• 2004

The control systems with friction cause the steady state error and slow response, because friction is a sensitive to the change of system condition and has highly nonlinear characteristics. To overcome these problems and do precise position control for a ball-screw system, we use Coulomb friction estimator and the sliding mode control(SMC) to compensate its negative effect. The applied SMC for tracking position has a characteristics of robust stability and reducing chattering, and is derived from the Lyapunov stability theorem and reaching condition. Compensating the estimated friction torque to the bounded disturbance term of the SMC's equivalent control input, it has a tracking performance better than the PID from the experimental results.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 추계학술대회 논문집(제1권)
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• pp.405-413
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• 2006

본 논문에서는 비선형 동적 마찰 성분을 효과적으로 보상하고 적응적으로 제어함으로써 차세대 항만 자동화 이송시스템으로 주목받고 있는 LMTT(linear motor-based transfer technology)의 위치 정밀도를 향상시키는 것을 목적으로 하고 있다. 셔틀카(shuttle car)와 컨테이너들의 다양한 중량과, 이로 인해 발생하는 동적 마찰 특성 파라미터들을 정확하게 추정할 수 있는 관측기를 설계하였다. 적응 backstepping 제어 기법을 적용하여 시스템이 안정하게 제어될 수 있도록 하는 제어기를 설계하였다. 시스템은 변화하는 환경에 대하여 높은 적응성을 가질 수 있어 여러 종류의 부하는 물론 마찰 특성의 변화에도 양호한 제어 특성을 유지할 수 있었다. 제안한 제어시스템의 타당성을 보여주기 위해 축소된 형태의 LMTT 시뮬레이터를 제작하여, 이에 대해 시뮬레이션과 실험만을 수행하여 제안하는 방법의 타당성과 실현성을 입증하고자 하였다.