• Journal of Power Electronics
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• 제18권2호
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.203-205
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• 2002

This paper presents the fault location estimation algorithm in transmission line using a recursive least square error method (RLSE). To minimize the computational burden of the digital relay a RLSE approach is used. Computer simulation results of the RLSE algorithm seem promising, indicating that it should be considered for further testing and evaluation.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.2
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• pp.1234-1238
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• 2004

A Controlled neural networks are proposed in order to measure nonlinear environments in adaptive and in realtime. The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between tile output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we have various experiments. And this controller call prove effectively to be control in the environments of various systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• 한국전자파학회논문지
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• 제12권5호
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• pp.802-809
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• 2001

이 논문에서는 VHF 대역에서 동작하는 주파수도약 송신기의 전력증폭기를 선형화한다. 적응 전치왜곡기(adaptive predistorter)를 사용하여 애널리그 다항식 선형화기를 전치왜곡기로 사용한다. 수렴 소도를 높이기 위하여 전치왜곡기의 출력신호와 후처리기의 출력신호 사이의 오차가 글로벌 최소치에 접근하도록 RLS(recursive least square) 적응 앨거리듬을 적용한다. 실험결과 설계된 선형 전력증폭기의 ACP(Adjacent Channel Power)는 10 dB 개선된다.

• 전기학회논문지
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• 제56권2호
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• pp.311-316
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• 2007

This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

• 전력전자학회논문지
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• 제5권6호
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• pp.575-583
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• 2000

본 논문에서는 이관성 시스템의 기계계 파라미터의 새로운 추정 알고리즘을 제안한다.RLS(Recursive Least Square) 알고리즘과 가속도정보를 이용하여 이관성 시스템의 부하의 관성, 전동기 관성 그리고 축강성을 추정하고 시뮬레이션과 실힘을 통해 제안된 기법의 유효성을 검증한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 하계학술대회 논문집 Vol.9
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.

• 한국공작기계학회논문집
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• 제11권6호
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• pp.98-104
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• 2002

In this study, we have developed an algorithm by attaching a camera at the end-effector of industrial six-axis robot in order to determine position and orientation of the camera system from cartesian coordinates. Cartesian coordinate as a starting point to evaluate for suggested algorithm, it was easy to confront increase of orientation vector for a linear line point that connects two points from coordinate space applied by recursive least square method which includes previous data result and new data result according to increase of image point. Therefore, when the camera attached to the end-effector has been applied to production location, with a calibration mask that has more than eight points arranged, this simulation approved that it is possible to determine position and orientation of cartesian coordinates of camera system even without a special measuring equipment.

• 전력전자학회논문지
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• 제6권5호
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• pp.446-452
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• 2001

본 논문에서는 Kharitonov 견실 제어 이론을 적용하여 유도 전동기 관성 변동에 대한 새로운 속도 제어기 설계기법을 제안한다. 정속도 운전을 하는 경우 관성의 변화는 운전 성능을 저하시키는 요인이 되며 운전 중 발생되는 관성의 변화는 제어기를 포함한 전체 시스템 특성방정식의 근을 이동함으로 시스템의 속응성에 영향을 주게된다. RLS (Recursive Least Square) 알고리즘을 이용하여 관성 변화를 추정하고 이를 기반으로 안정도 마진을 포함하는 속도 제어기 이득을 설정한다. 또한 시뮬레이션과 실험을 통해 제안된 기법의 유효성을 검증한다.