• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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• pp.738-741
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• 2004

The overall performance of AC servo system is greatly affected by the uncertainties of unpredictable mechanical parameter variations and external load disturbances. Therefore, to compensate this problem, it is necessary to know different parameters and load disturbances subjected to position/speed control. This paper proposes an online identification method of mechanical parameters/load disturbances for AC servo system using Support Vector Regression (SVR). The proposed methodology advocates analytic parameter regression directly from the training data, rather than adaptive controller and observer approaches commonly used in motion control applications. The experimental results demonstrate that the proposed SVR algorithm is appropriate for control of unknown servo systems even with large measurement noise.

• 전력전자학회논문지
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• 제10권5호
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• pp.468-480
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• 2005

서보 시스템의 전체 제어 성능은 기계적 상수의 변화와 부하 토크의 영향을 크게 받는다. 그러므로 서보 시스템의 성능을 향상시키기 위해서는 기계적 상수와 부하 토크를 정확히 알 필요가 있다. 본 논문에서는 Support Vector Regression(SVR)을 이용한 기계적 상수와 부하 토크 추정 알고리즘을 제안한다. 실험 결과는 제안된 SVR 알고리즘이 서보 시스템의 기계적 상수와 부하 토크를 정확하게 추정하고 있음을 보여준다.

• 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.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.207-213
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• 2000

This paper introduces a high-performance speed control system based on artificial neural networks(ANN) to estimate unknown parameters of a DC servo motor. The goal of this research is to keep the rotor speed of the DC servo motor to follow an arbitrary selected trajectory. In detail, the aim is to obtain accurate trajectory control of the speed, specially when the motor and load parameters are unknown. By using an artificial neural network, we can acquire unknown nonlinear dynamics of the motor and the load. A trained neural network identifier combined with a reference model can be used to achieve the trajectory control. The performance of the identification and the control algorithm are evaluated through the simulation and experiment of nonlinear dynamics of the motor and the load using a typical DC servo motor model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2076-2080
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• 2005

Study in this paper concerns the optimal $H_{2}$ integral servo problems for linear crane model systems via the constraints of the derivatives of state variables added to the standard constraints. It is shown in the paper that the derivative state constrained optimal $H_{2}$ integral servo problems can be reduced to the standard optimal $H_{2}$ control problem. The main subject of the paper is to apply the results of derivative state constrained $H_{2}$ integral servo theorem in crane system. The effect of our proposed controller with respect to mitigate an under damping for crane model system is also verified.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1960-1965
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• 2005

This paper presents theory for stability analysis and design of a servo system for a MIMO Wiener system with nonlinear uncertainty. The Wiener system consists of a linear time-invariant system(LTI) in cascade with a static nonlinear part ${\psi}$(y) at the output. We assume that the uncertain static nonlinear part is sector bounded and decoupled. In this research, we treat the static nonlinear part as multiplicative uncertainty by dividing the nonlinear part ${\psi}$(y) into ${\phi}$(y) := ${\psi}$(y)-y and y, and then we reduce this stabilizing problem to a Lur'e problem. As a result, we show that the servo system with no steady state error for step references can be constructed for the Wiener system.

• 한국전자통신학회논문지
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• 제7권3호
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• pp.553-558
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• 2012

최근에 로봇에서 다축 모션 제어를 위한 노력이 계속되고 있다. 본 논문에서는 로봇에서 다축 모션 제어를 쉽게 할 수 있는 AC 서보 드라이버를 구현 기법을 제안한다. 제안한 방법은 먼저 상위의 제어기 단과 드라이버단 사이의 통신을 위해 WDM 방식을 적용한 싱글 광 코어 기반의 양방향 광 EtherCAT 통신 기술을 적용하여 구현한다.

• 한국군사과학기술학회지
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• 제3권1호
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• pp.38-46
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• 2000

In this paper, robust depth and course controllers of AUV(autonomous underwater vehicles) using LMI-based H$_{\infty}$ servo control are proposed. The $H_{\infty}$ servo problem is modified to an $H_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The robust depth and course controllers are designed to be satisfied the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under sea wave and tide disturbances. The performances of the designed controllers are evaluated by computer simulations, and these simulation results show the applicability of the proposed robust depth and course controller.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.14-17
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• 1999

This paper describes the controller for the improving speed control the AC servo motor. The microprocessor provides an output to the difference in command. The servo system improves the characteristics of speed control. When the motor is running at the same speed as set by the reference signal, the speed encoder also provides a signal the same frequency. Thus, the microprocessor controlled digital techniques enable to realize the flexible performance and control which was possible with time constant. We can know that PI control using neural networks by 80196 can control efficiently speed of AC Servo motor. Finally experimental results prove excellent performance of this control system. The system can be adaptable to CNC machine.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.812-814
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• 1999

In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.