• 전기전자학회논문지
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• 제2권2호
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• pp.255-262
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• 1998

The neural network can roughly be classified as the specialized control, indirect control and general schemes. Neural network is adopted for MPPT of solar array. And back propagation algorithm also is used to train neural network controller. We investigate the possibilities of $P_{max}$ control using the neural networks, and then we also examine about operating the solar cell at an optimal voltage comprise of temperature compensated voltage with boost converter. Proposed boost converter of MPPT system is studied by simulation and is implemented by using a microprocessor(80c196kc) which controls duty ratio of the boost converter.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2011년도 전력전자학술대회
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• pp.93-94
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• 2011

The use of boost chopper in Permanent Magnet Synchronous Generator (PMSG) aims to capture maximum power at any wind speed condition. It is reached by adjusting the duty cycle of boost chopper. In this paper, fuzzy logic algorithm is used to find the duty cycle value which yields the maximum power output. This control scheme is verified by PSIM simulation. Another MPPT method is also simulated as a comparison.

• Journal of Power Electronics
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• 제15권6호
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• pp.1664-1672
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• 2015

This paper proposes a series arc fault detection algorithm which incorporates peak voltage and harmonic current detectors for single-phase boost power factor correction (PFC) rectifiers. The series arc fault model is also proposed to analyze the phenomenon of the arc fault and detection algorithm. For arc detection, the virtual dq transformation is utilized to detect the peak input voltage. In addition, multiple combinations of low- and high-pass filters are applied to extract the specific harmonic components which show the characteristics of the series arc fault conditions. The proposed model and the arc detection method are experimentally verified through a boost PFC rectifier prototype operating under the grid-tied condition with an artificial arc generator manufactured under the guidelines for the Underwriters Laboratories (UL) 1699 standard.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.743-744
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• 2008

By using DirectX technology, an improved Visual Monitoring System implemented in this paper. The proposed Visual Monitoring System is developed based on the S3C2440 processor. The Windows CE 5.0 is adopted as an operating system, and Visual Monitoring System transfer image 15 frame per second using UDP/IP and by using AdaBoost Algorithm, detect face region and save face image.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.211-219
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• 2018

This paper designs a nonlinear PI-type controller for the robust control of a boost DC-DC converter using a particle swarm optimization (PSO) algorithm. Based on the common knowledge that the transient responses can be improved if the P and I gains increase when the transient error is big, a nonlinear PI-type control design method is developed. A design procedure to autotune the nonlinear P and I gains is given based on a PSO algorithm. The proposed nonlinear PI-type controller is implemented in real time on a Texas Instruments TMS320F28335 floating-point DSP. Simulation and experimental results are given to demonstrate the effectiveness and practicality of the proposed method.

• Journal of Power Electronics
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• 제13권6호
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• pp.1000-1007
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• 2013

This paper proposes a sliding-mode-based direct power control (DPC) method in a three-phase boost rectifier without the use of a voltage sensor. This sliding-mode-based DPC is used to improve transient-state response characteristics. This DPC can eliminate voltage sensors by calculating a voltage using a sensorless method, thus considerably reducing cost. This DPC first presents an effective algorithm that does not significantly affect the previous performance and does not need a voltage sensor. Thereafter, the effectiveness of the algorithm is verified by simulations and experiments.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.153-159
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• 2012

In photovoltaic system, the characteristic of photovoltaic module such as open circuit voltage and short circuit current will be changed because of cell temperature and solar radiation. Therefore, a boost converter of the PV system connects between the output of photovoltaic system and DC link capacitor of grid connected inverter as controlling duty ratio for maximum power point tracking(MPPT). This paper shows the dynamic characteristic of the boost converter by comparing single-loop control algorithm and two-loop control algorithm using both analog and digital control. The proposed both compensation method has been verified with computer simulation and simulation results obtained demonstrate the validity of the proposed control schemes.

• 한국항해항만학회지
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• 제31권10호
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• pp.839-844
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• 2007

본 논문은 벅, 부스터, 벅-부스트 등의 부이용 DC-DC 컨버터 성능에 대하여 기술하였다. PV 시스템과 연계한 컨버터에 관한 특성이 고려된 동작특성 및 충전효율에 대하여 분석하였다. 그것은 MPPT 알고리즘과 더불어 수행되었다. 컨버터를 위한 기본 스위칭 방정식을 기술하고, 스위칭 상태에 따른 방정식을 해석하였다. 이 해석은 부이선택에 초점을 맞추고 있으며, 또한 컨버터 동작 및 제안한 알고리즘의 성능을 관찰하였다. 마지막으로 부이에 적합한 DC-DC 컨버터를 제안하였으며, 벅 컨버터에 대한 특성실험도 수행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.131-133
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• 2008

In this paper, the control method of extracting maximum power from the seaflow energy is proposed. This Paper describes a variable speed seaflow generation system with Permanent magnet synchronous motor, bridge rectifier, buck-boost converter and Fuzzy controller. In this Proposed seaflow generation system, the duty ratio of buck-boost converter is controlled by the fuzzy controller. An advantage of MPPT control method presented in this paper don't need to use the characteristic of seaflow turbine at various seaflow speed and measure the tidal speed and the rotating speed of tidal turbine. Therefore, the Proposed system has the characteristics of lower cost, higher efficiency and lower complexity. The effectiveness of algorithm is simulated based on Matlab Simulink.

• ETRI Journal
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• 제32권5호
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• pp.761-765
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• 2010

In this paper, we introduce an improved adaptive boosting (AdaBoost) classifier and its application, a disguised-face discriminator that discriminates between bare and disguised faces. The proposed classifier is based on an AdaBoost learning algorithm and regression technique. In the process, the lookup table of AdaBoost learning is utilized. The proposed method is verified on the captured images under several real environments. Experimental results and analysis show the proposed method has a higher and faster performance than other well-known methods.