• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2375-2377
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• 2003

본 논문에서는 2자유도를 가지는 평면형 로봇매니퓰레이터의 궤도제어에 슬라이딩모드 제어기법을 도입한 비 간섭 제어기법을 적용하였다. 따라서 종래의 선형구조해석에 근간을 둔 비 간섭제어와는 달리 파라미터 오차 및 비선형에 의한 영향을 억제할 수 있는 강인한 제어기 설계가 가능하며 매니퓰레이터의 궤도제어에 적용하여 제안한 제어기법의 유용성을 확인하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.2
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• pp.152-162
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• 2008

This paper presents a sliding mode controller (SMC) to directly control the active and reactive powers of a doubly ffd induction generator (DFIG) for wind turbines. Sliding-mode control (SMC) and space-vector modulation (SVM) are combined to ensure high-performance operation. SMC scheme is designed to provide robust and fast power controls without frame transformation and current controller used in the conventional FOC drive. Simulation results and experimental results demonstrate that proposed methods preserve the effectiveness and robustness during variations of active and reactive power.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.275-284
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• 2016

Accurate electricity demand forecasts is essential in reducing energy spend and preventing imbalance of the power supply. In forcasting electricity demand, we considered double seasonal Holt-Winters model and TBATS model with sliding window. We selected a specific time zone as the reference line of daily electric demand because it is least likely to be influenced by external factors. The forecasting performance have been evaluated in terms of RMSE and MAPE criteria. We used the observations ranging January 4, 2009 to December 31 for testing data. For validation data, the records has been used between January 1, 2012 and December 29, 2012.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.293-299
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• 2018

The weather has a lot of influence on the cultivation of crops. Weather information on agricultural crop cultivation areas is indispensable for efficient cultivation and management of agricultural crops. Despite the high demand for agricultural weather, research on this is in short supply. In this research, we deal with the production method of agricultural weather in Jeollanam-do, which is the main production area of onions through GloSea5 and deep learning. A deep neural network model using the sliding window method was used and utilized to train daily weather prediction for predicting the agricultural weather. RMSE and MAE are used for evaluating the accuracy of the model. The accuracy improves as the learning period increases, so we compare the prediction performance according to the learning period and the prediction period. As a result of the analysis, although the learning period and the prediction period are similar, there was a limit to reflect the trend according to the seasonal change. a modified deep layer neural network model was presented, that applying the difference between the predicted value and the observed value to the next day predicted value.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.703-706
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• 1999

In this paper, robust vibration control of a one-link flexible robot arm based on variable structure system is discussed. We derive dynamic equations of it using a Lagragian assumed modes method based on Bernoulli-Euler beam theory. The optimal sliding surface is designed and the problem of chattering is also solved by the adoptation of a continuous control law within a small neighborhood of the switching hyperplane.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.341-341
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• 2000

This paper presents a sliding mode control(SMC) design method for single input linear systems with uncertainties and time delay in the state. We define a sliding surface for the augmented system with a virtual state which is defined from the nominal system. We make a virtual state from optimal control input using LOR(Linear Quadratic Regulator) and the states of the nominal system. We construct a controller that combines SMC with optimal controller. The proposed sliding mode controller stabilizes on the overall closed-loop system.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.211_212
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• 2009

부하 모델링이 전력계통의 해석과 제어에 미치는 영향력은 매우 크다. 정확한 부하모델링을 위해 최근에는 측정기반의 부하 모델링이 많이 연구되고 있다. 부하모델링 알고리즘은 먼저 모델의 구조를 정하고, 그 모델에 적합한 파라미터를 산정하는 작업으로 이루어진다. 파라미터 산정에는 최소자승법이 사용되었다. 이 최적화 과정에서 알고리즘을 통해 나온 계산값과 측정값의 차이가 최소가 되도록 파라미터를 산정하였다. 슬라이딩 윈도우(sliding window)의 개념을 도입해, 실시간으로 변화하는 부하의 동특성을 반영할 수 있는 온라인 부하모델링을 수행하였다. 실측 데이터의 취득을 위해 학교 부하에 PMU를 설치하였다. 본 논문에서는 사례 연구를 위해 실시간 시뮬레이터의 데이터를 이용하였고, 정적 ZIP 모델을 통해 알고리즘의 정확성을 검토하였다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1601-1607
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• 2016

Recently, weather information has been increasingly used in various area. This study presents the necessity of hourly weather information for electricity demand forecasting through correlation analysis and multivariate regression model. Hourly weather data were collected by Meteorological Administration. Using electricity demand data, we considered TBATS exponential smoothing model with a sliding window method in order to forecast electricity demand. In this paper, we have shown that the incorporation of weather infromation into electrocity demand models can significantly enhance a forecasting capability.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.395-401
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• 2014

Magnetic levitation systems using the attraction force of electromagnets have many constraints according to the variation of air gap and the nonlinearity of electromagnetic force and inductances. As a result of these constraints, the nonlinear control of a magnetic levitation system has been improved by the latest advanced processors and accurate measurement system which can overcome problems such as many constraints and nonlinearity. This paper concentrates on the modeling of a nonlinear magnetic levitation system and an application of an exponential reaching law based sliding mode controller using the exponential reaching law which is one of the most robust controllers against external unexpected disturbances or parameter fluctuations. Controllability of a magnetic levitation system using the sliding mode control algorithm and robustness against parameter fluctuations have been verified through the experimental results.

• KIEAE Journal
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• v.17 no.4
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• pp.59-65
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• 2017

Purpose: Thermal performance and air tightness of window are improved for the building energy efficiency. As the deteriorated houses are increased, the improve measures with low cost and easy installation are developed in the energy performance of window. Attached glazing and windbreak can be easily applied to the window with low cost. In this paper, the effect of the attached glazing and windbreak on the thermal performance and air tightness of window is analyzed as the measure to improve performance of window. Method: Thermal transmittance of glazing is evaluated through WINDOW simulation according to thickness of attached glazing and air cavity. Based on the simulation results, thermal transmittance, air tightness and condensation resistance performance of four cases are tested according to Korea standards. One type of PVC sliding double window is chosen as the specimen. For the analysis on low performance of window, the outside of window is excluded in the PVC sliding double window. Result: This study shows that thermal performance of glazing can be increased by the application of attached glazing. Furthermore, lower thermal performance of glazing can obtain the higher effect of attached glazing. The application of attached glazing and windbreak can effect on increasing thermal performance and air tightness of window.