• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2807-2810
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• 2003

In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 춘계학술대회
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• pp.579-582
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• 2011

가변 메카니즘은 키오스크를 이용하는 사용자의 키와 위치를 초음파 센서를 통하여 감지하고, 이를 통하여 적정한 높이와 키오스크의 방향을 조절한다. 본 논문에서는 가변형 키오스크의 높이와 방향 제어를 위하여 ADALINE-퍼지 논리 시스템 제어 방식을 제안한다. 제안한 방식의 유용성을 확인하기 위하여 가변형 키오스크 시스템이 사용자의 방향과 높이에 따른 제어 동작을 제대로 수행하는지 대하여 Widrow-Hoff 델타 규칙과 실험을 통하여 성능을 비교 검토 하였다.

• Journal of Power Electronics
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• 제9권3호
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• pp.386-395
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• 2009

In this paper, a new control algorithm for the dynamic voltage restorer (DVR) is proposed to regulate the load terminal voltage during various power quality problems that include sag, swell, harmonics and unbalance in the voltage at the point of common coupling (PCC). The proposed control strategy is an Adaline (Adaptive linear element) Artificial Neural Network (ANN) and is used to control a capacitor supported DVR for power quality improvement. A capacitor supported DVR does not need any active power during steady state because the voltage injected is in quadrature with the feeder current. The control of the DVR is implemented through derived reference load terminal voltages. The proposed control strategy is validated through extensive simulation studies using the MATLAB software with its Simulink and SimPower System (SPS) toolboxes. The DVR is found suitable to support its dc bus voltage through the control under various disturbances.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.429-434
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• 2005

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 추계학술대회
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• pp.136-137
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• 2019

본 논문에서는 ADALINE (Adaptive-Linear-Neuron) 구조의 ANN(Artificial Neural Network)을 이용한 3상 PWM 컨버터의 개방고장 진단 방법에 대해 제안한다. 3상 PMW 컨버터에서 스위치의 개방고장이 발생한 경우 보호회로에 의해 시스템이 중단되지 않으며, 개방고장으로 인한 상전류의 고조파와 직류 성분에 의해 주변 기기에 고장에 의한 파급효과가 나타날 수 있다. 이에 본 논문에서는 ADALINE을 이용하여 각 상의 THD(Total Harmonics Distortion)와 직류 성분 얻고 대소비교를 통해 개방고장이 발생한 스위치를 진단하는 방법에 대해 제안한다.

• Journal of Power Electronics
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• 제11권5호
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• pp.751-758
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• 2011

This paper presents an effective robust predictive control scheme for the active power filter (APF) using a smith-predictor based current regulator, which show superior features when compared to proportional-integral (PI) controllers in terms of an enhanced closed-loop bandwidth and an improved current tracking accuracy. A moving average filter (MAF) is implemented using a field programmable gate array (FPGA) for signal pre-processing to eliminate the switching ripple contamination. An adaptive linear neural network (ADALINE) is used for individual harmonic estimation to achieve selective compensation purpose. The effectiveness and validity of the devised control algorithm are confirmed by extensive simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.28-35
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• 2010

This paper presents new Adaptive Linear Combination Structure (ADALINE) for tracking/estimating voltage-current phasor and frequency of power system. To estimate the phasors and frequency from sampled data, the algorithm assumes that orthogonal coefficients and speed of angular frequency of power system are unknown parameters. With adequate sampled data, the estimation problem can be considered as a linear weighted least squares (LMS) problem. In addition to determining the phasors (orthogonal coefficients), the procedure estimates the power system frequency. The main algorithm is verified through a computer simulation and data from field. The proposed algorithm is tested with transient and dynamic behaviors during power swing, a step change of frequency upon islanding of small generators and disconnection of load. The algorithm shows a very high accuracy, robustness, fast response time and adaptive performance over a wide range of frequency, from 10 to 2000 Hz.

• 정보교육학회논문지
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• 제9권2호
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• pp.167-176
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• 2005

교육현장에서 발생하는 여러 가지 의사결정 사항들을 효과적으로 처리하는 것은 매우 중요한 이슈로 부각되고 있다. 예를 들어, 교육인적자원부 입장에서 전국 초등학교를 대상으로 교육정보화 분야에 투자를 기획할 때 정확하고 효율적인 의사결정 과정은 국가적 차원에서 매우 중요한 사항인 것이다. 현재 이상과 같은 일련의 과정을 시행하기 위하여 현장의 설문조사나 관련 전문가를 활용한 기획이 이루어지고 있는 실정이 다. 그러나, 정보 기술분야의 급격한 발전으로, 의학이나 경영분야 등에서는 다양한 의사결정지원 도구 활용을 통한 최상의 의사 결정 방법을 찾고 있다. 이 같은 이유로 본 논문에서는 신경망의 ADALINE 알고리즘을 활용하여 교육분야에서 적용 가능한 의사결정 시스템 모델을 설계하였으며 또한 시뮬레이션을 통하여 구현 모델의 검증을 수행하였다. 개발된 교육용 의사결정 시스템으로 교육현장에서 발생하는 다양한 의사결정 사항들을 효과적으로 처리할 수 있을 것이다.

• Journal of Power Electronics
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• 제11권2호
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• pp.228-236
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• 2011

The ${\Delta}\;V_{10}$ or 10-Hz flicker index, as a common method of measurement of voltage flicker severity in power systems, requires a high computational cost and a large amount of memory. In this paper, for measuring the ${\Delta}\;V_{10}$ index, a new method based on the Adaline (adaptive linear neuron) system, the FFT (fast Fourier transform), and the PSO (particle swarm optimization) algorithm is proposed. In this method, for reducing the sampling frequency, calculations are carried out on the envelope of a power system voltage that contains a flicker component. Extracting the envelope of the voltage is implemented by the Adaline system. In addition, in order to increase the accuracy in computing the flicker components, the PSO algorithm is used for reducing the spectral leakage error in the FFT calculations. Therefore, the proposed method has a lower computational cost in FFT computation due to the use of a smaller sampling window. It also requires less memory since it uses the envelope of the power system voltage. Moreover, it shows more accuracy because the PSO algorithm is used in the determination of the flicker frequency and the corresponding amplitude. The sensitivity of the proposed method with respect to the main frequency drift is very low. The proposed algorithm is evaluated by simulations. The validity of the simulations is proven by the implementation of the algorithm with an ARM microcontroller-based digital system. Finally, its function is evaluated with real-time measurements.

• Journal of Electrical Engineering and Technology
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• 제8권4호
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• pp.863-871
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• 2013

Control of pitch angle of turbine blades is among the controlling methods in the wind turbines; this measure is taken for managing mechanical power generated by wind turbine in different wind velocities. Taking into account the high significance of the power generated by wind turbine and due to the fact that better performance of pitch angle is followed by better quality of turbine-generated power, it is therefore crucially important to optimize the performance of this controller. In the current paper, a PI controller is primarily used to control the pitch angle, and then another controller is designed and replaces PI controller through applying a new strategy i.e. alternating two ADALINE neural networks. According to simulation results, performance of controlling system improves in terms of response speed, response ripple, and ultimately, steady tracing error. The highly significant feature of the proposed intelligent controller is the considerable stability against variations of wind velocity and system parameters.