• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.102-106
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• 2000

본 논문은 뉴로-퍼지 모델의 구조학습을 이용하여 한 시간 앞의 전력 수요를 예측하는 체계적인 방법을 제안한다. 제안된 예측시스템은 시간 단위로 뉴로-퍼지 모델을 재학습하기 위해서 필요한 초기 구조를 요일 유형과 시간 별로 미리 생성하고, 이를 초기 구조 뱅크에 저장한다. 예측이 수행되는 시점의 요일 유형에 따라 선택된 초기 구조를 이용하여 뉴로-퍼지 모델을 초기화하고, 학습하고, 예측을 수행한다. 제안된 방법의 실효성을 검증하기 위해 1996년과 1997년의 실제 전력 수요 데이터를 이용하여 모의 실험을 수행한다. 실험결과 제안된 방법은 기존의 다층 퍼셉트론을 이용한 방법과 비교하여 예측의 정확도 측면과 신뢰도 측면에서 모두 향상된 결과를 얻는다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.24-26
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• 2005

This paper presents a framework for determining control strategies against unwanted tripping actions of relay operation that plays a very important role in cascading events leading to voltage collapse. The framework includes an algorithm for quick identification of possible zone 3 relay operation during voltage instability. The proposed approach comes up with control strategy of load shedding at the selected location with active power and relay margin criteria. In addition, Quasi Steady-State (QSS) simulation is employed to obtain time-related information which is valuable for both the timing and amount of control. The methodology is demonstrated through the modified New England 39-bus system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.366-368
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• 2006

Electronic warfare Support(ES) system measures pulse characteristics for received RF signals that received from all directions. ES system discriminates the pulse trains that have a rule, correlationship, continuance from collected data and analyze the characteristics of the data, and identify the emitters by comparison with emitter identification data(EID). Because pulse density is very high and various signal source exists at modem signal environments, high-speed and accurate signal analysis is needed for realtime countermeasure to emitters. Grouping alleviates the load of signal analysis process and supports reliable analysis. In this paper, we suggest an adaptive clustering scheme regarding signal patterns.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.427-431
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• 1996

The MRAS proposed by Schauder [8] is modified to improve robustness to the change of load torque and/or the variation of the stator resistance. The difference between the voltage and the current model is fed into the current model via proportional and integral gains. In order to generalize the MRAS, supposing that the rotor speed is time varying, we add a compensating term to the current model. It does not alter the Popov's integral inequality condition. Also, the asymptotic stability of the modified MRAS (MMRAS) is shown with the stability proof technique as in the original paper. By the simulation works, it is verified that the MMRAS obtains improved performance than the original MRAS.

• 제어로봇시스템학회논문지
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• 제22권5호
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• pp.339-345
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• 2016

This paper presents a robust speed control of an autonomous vehicle using a disturbance observer. For the purpose, the transfer function of speed dynamics of an autonomous vehicle is identified using step response data. Based on the identified transfer function, model based PID (Proportional-Integral-Derivative) control is designed. In order to design a robust control against load variations on the vehicle, a disturbance observer (DOB) based control is devised. The performance of the designed DOB based control is demonstrated by real experiments.

• Interaction and multiscale mechanics
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• 제3권4호
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• pp.321-331
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• 2010

A new technique is proposed for bridge structural damage detection based on spatial wavelet analysis of the time history obtained from vehicle body moving over the bridge, which is different from traditional detection techniques based on the bridge response. A simply-supported Bernoulli-Euler beam subjected to a moving spring-mass unit is established, with the crack in the beam simulated by modeling the cracked section as a rotational spring connecting two undamaged beam segments, and the equations of motion for the system is derived. By using the transfer matrix method, the natural frequencies and mode shapes of the cracked beam are determined. The responses of the beam and the moving spring-mass unit are obtained by modal decomposition theory. The continuous wavelet transform is calculated on the displacement time histories of the sprung-mass. The case study result shows that the damage location can be accurately determined and the method is effective.

• Journal of Power Electronics
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• 제10권3호
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• pp.270-276
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• 2010

In this paper, a capacitance estimation scheme for DC-link capacitors for single-phase AC/DC PWM converters is proposed. Under the no-load condition, a controlled AC current (30[Hz]) is injected into the input side, which then causes AC voltage ripples at the DC output side. Or, a controlled AC voltage can be directly injected into the DC output side. By extracting the AC voltage/current and power components on the DC output side using digital filters, the capacitance value can be calculated, where the recursive least squares (RLS) algorithm is used. The proposed methods can be simply implemented with software only and additional hardware is not required. From the experiment results, a high accuracy estimation of capacitances less than 0.85% has been obtained.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.149-152
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• 1992

A simple and practial equivalent technique has been presented in this study. Arbitrary number of bus system can be aggregated to the equivalent one-bus system, equivalents are totel real, and reactive bus powers and T/L losses viewing form boundary buses. Variables to be determined are line impedance between boundary buses and the equivalent bus, voltage and angle of that bus. IEEE 14 bus system is used to demonstrate the proposed method. even in contingency cases very good results have been obtained

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.239-241
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• 1992

In this paper, back-propagation neural network is used for the identification and trajectory control of a DC motor. The neural network is trained to identify the unknown nonlinear dynamics of the motor and load and the trained neural network is used for speed control of the DC motor to have good performance. Simulation results show the good performance of the control system based on the neural network under arbitrarily chosen speed trajectories.

• 대한기계학회논문집A
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• 제24권10호
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• pp.2451-2460
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• 2000

In order to minimize straightness error of deflected shaft, a geometric adaptive straightness controller system is studied. A multi-step straightening and a three-point bending process have been developed for the geometric adaptive straightness controller. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and real-time hydraulic control methodology are studied for the three-point bending process. By deflection pattern analysis and fuzzy self-learning method in the multi-step straightening process, a straightening point and direction, desired permanent deflection and supporting condition are determined. An automatic straightening machine has been fabricated for rack bars by using the developed ideas. Validity of the proposed system is verified through experiments.