• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.140-143
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• 1991

This paper describes a compensation method for the rotor resistance variation of induction machines in speed sensor-less vector control system using MRAS(model reference adaptive system). In case of rotor resistance variation, the analysis of the conventional speed sensor-less vector control system using MRAS is presented and the compensation method for rotor resistance variation using Fuzzy logic is proposed. In order to confirm the performance of the proposed algorithm, computer simulation is performed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.50-52
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• 2006

This paper Proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1656_1657
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• 2009

This paper presents a new method for estimating rotor resistance of induction motor. The rotor resistance changes dramatically with temperature and frequency. Speed is controlled by PID as it is simplest and most intuitive control method. The change in rotor resistance has a great influence on the performance of IM. In this paper rotor resistance is estimated using Non Linear Disturbance Observer. The model uncertainty and system non linearity are treated as disturbance in this method. Using NDO it does not require an accurate dynamic model to achieve high precision motor control. Controller with NDO has more superior tracking performance. Simulation results are presented to show the validity of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.647-648
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• 2015

최근 최저효율제를 대비한 프리미엄급 고효율 전동기의 필요성이 대두됨에 따라 유도전동기를 대체할 수 있는 고효율 전동기로써 영구자석 매입형 동기 릴럭턴스 모터(PMA-SynRM)가 각광받고 있다. 하지만 모터의 속도와 토크를 제어하기 위해 회전자 속도와 위치 정보를 측정할 수 있는 센서가 필요하고, 이 때 센서 설치의 공간적 문제, 센서의 유지/보수 및 시스템의 추가 비용 발생 등 많은 문제점들이 발생한다. 따라서 센서를 제거하기 위한 센서리스 위치 및 속도 제어에 관한 연구가 폭 넓게 진행되고 있다. 하지만 모터를 운전함에 따라 저항이나 역기전력 상수, 인덕턴스 등의 제정수의 변동이 발생하게 되고 센서리스 제어 시 이러한 변동에 의해서 추정 속도 및 위치에 오차가 발생하게 된다. 본 논문에서는 이러한 오차의 보상을 위해 MRAS(Model Reference Adaptive System) 방식을 적용한 센서리스 제어를 제안한다.

• 한국정밀공학회지
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• 제22권2호
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• pp.70-78
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• 2005

In this paper, a novel rotor flux estimation method of an induction motor using support vector regression(SVR) is presented. Two well-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. Training of SVR which the theory of the SVR algorithm leads to a quadratic programming(QP) problem. The proposed SVR rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of proposed algorithm are throughly verified through numerical simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 학술대회 논문집 전문대학교육위원
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• pp.113-115
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• 2001

This paper presents the rotor parameter identification based on the MRAS theory and the speed estimation using ANN for the sensorless vector control of induction motor. The motor speed is estimated using ANN model which contains the rotor parameter. And the rotor parameter is identified using MRAS scheme which contains the rotor speed. The rotor speed estimate converges to its actual value as the rotor parameter error converges toward the zero. The simulation using Matlab/Simulink is performed to show the effectiveness of the proposed scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.357-359
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• 1994

This paper consists of the vector control of three phase induction motors which has robustness against disturbances and parameter variations by the TDOF (Two Degree Of Freedom) theory. Using the TDOF theory, induction motor is robustly controlled for resistance variations and disturbances. Adaptive observer is used for the purpose of estimating the stator fluxes, the stator currents, and the parameters. The proposed control netted is verified by computer simulations.

• 제어로봇시스템학회논문지
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• 제7권2호
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• pp.125-130
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• 2001

This paper presents an indirect field-oriented (IFO) induction motor position servo drives which uses the model following adaptive controller with the artificial neural network(ANN)-based rotor resistance estimator. The model reference adaptive system(MRAS)-based 2-layer ANN estimates the rotor resistance on-line and a linear model-following position controller is designed by using the estimated the rotor resistance value. At the end, a fuzzy logic system(FLS) is added to make the position controller robust to the external disturbances and the parameter variations. The simulation results show the effectiveness of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.1123-1125
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• 2000

This paper presents the speed estimation using ANN and the rotor parameter Identification based on the MRAS theory for the sensorless induction motor drives. The motor speed is estimated using ANN model which contains the rotor parameter. And the rotor parameter is identified using MRAS scheme which contains the rotor speed. The rotor speed estimate converges to its actual value as the rotor parameter error converges toward the zero. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 추계학술대회 논문집
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• pp.65-68
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• 2001

In the vector control methods of induction motor, the stator current is divided into the flux and torque component current. By controlling these components respectively, the methods control independently flux and torque as in the DC motor and improve the control effects. To apply the vector control methods, the position of the rotor current is identified. The indirect vector control use the parameters of the machine to identify the position of rotor flux. But due to the temperature rise during machine operation, the variation of rotor resistance degrades the vector control. To solve the problem, the q-axis is aligned to reference frame without phase difference by comparing the real flux component with the reference flux component. Then to compensate the slip, PI controller is used. The proposed method keeps a constant slip by compensating the gain of direct slip frequency when the rotor resistance of induction motor varies. To prove the validations of the proposed algorithm in the paper, computer simulations is executed.