• 융합보안논문지
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• 제5권3호
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• pp.33-41
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• 2005

네트워크 및 인터넷시장의 발전과 더불어 침해사고도 급증하고 있으며 그 방법도 다양해지고 있다. 이를 방어하기 위해 여러 가지 보안시스템이 개발되어 왔으나 관리자가 수동적으로 침입을 차단하는 형식을 띄고있다. 본 논문에서는 침입탐지 시스템의 패킷 분석능력과 공격에 대한 실시간 대응성을 높이기 위하여 리눅스 OS에서 방화벽기능을 담당하는 넷필터를 이용해 침입탐지 및 차단시스템을 설계하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.31-34
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• 1998

In this paper, a Single-phase Active Rectifier(SAR) with high power factor capability for inverter air-conditioner is adopted for satisfying the international standards of input current harmonics, IEC 1000-3-2. Comparing the conventional boost power factor correction circuit, one diode drop is reduced in the power flow path of the SAR circuit, so the system efficiency is improved. To apply the control IC, such as UC3854, ML4821 and so forth, to the SAR, the adequate sensing circuits are proposed. The design rules of passive components and two control loops are also presented. The prototype SAR circuit with 3㎾ power consumption is builted and tested to verify the operation of the proposed circuit.

• 한국정보처리학회논문지
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• 제7권4호
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• pp.1160-1168
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• 2000

Due to the increase in importance of factory-automation (FA) in the field of production, the importance of he autonomous guided vehicle's (AGV) role has also increased. This paper is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an behavior-based system evolving by itself is also being considered. In this paper, constructed an active and effective AGV fuzzy controller to be able to carry out self-organization. To construct it, we tuned suboptimally membership function using a genetic algorithm (GA) and improved the control efficiency by self-correction and the generation of control rules.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.242-247
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• 2002

According to increase of the factory-automation(FA) in the field of production, the importance of the autonomous guided vehicle's(AGV) role has also increased. This paper is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an behavior-based system evolving by itself is also being considered. In this Paper, we constructed an active and effective AGV fuzzy controller to be able to carry out self-organization. To construct it, we tuned suboptimally membership function using a genetic algorithm(GA) and improved the control efficiency by self-correction and the generation of control rules.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.393-396
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• 2011

In this paper, we propose a constrained alternating least squares nonnegative matrix factorization algorithm (cALSNMF) to detect active brain regions from single subject's task-related fMRI data. In cALSNMF, we define a new cost function which considers the uncorrelation and noisy problems of fMRI data by adding decorrelation and smoothing constraints in original Euclidean distance cost function. We also generate a novel training procedure by modifying the update rules and combining with optimal brain surgeon (OBS) algorithm. The experimental results on visuomotor task fMRI data show that our cALSNMF fits fMRI data better than original ALSNMF in detecting task-related brain activation from single subject's fMRI data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1149-1150
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• 2007

In this paper, operation of isolated current-fed full-bridge converter with active clamp is investigated by simulation and experiments. Experimental waveforms show a good agreement with the corresponding simulation results. Further, losses such as conduction loss, turn-on/off loss of MOSFETs and diodes are measured and their characteristics in the converter is addressed. 200W prototype DC-DC converter is developed for verification of the derived operating modes, design rules and loss analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2045-2047
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• 2001

In this paper, we proposed the representation method of specification and the control rules fork FMS by TPL. To increase productivity and resource utilization, it is desirable to have more active jobs in the system, but the more active jobs there are, the more easily deadlock occur. Therefore, it is very important that the real-time deadlock control to disable deadlock. In this paper, we performed the system modeling by the CROPN(Colored Resource -Oriented Petri Net) and the necessary -sufficient condition check to disable deadlock. We proposed the supervisory control system that can be the real-time monitoring for deadlock free through a necessary-sufficient condition by CROPN modelling, and designed the logic controller of the extended process using TPL.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.41.4-41
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• 2001

In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.

• 로봇학회논문지
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• 제16권2호
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• 한국지능시스템학회논문지
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• 제9권6호
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• pp.598-604
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• 1999

본 논문에서는 능동형자기베어링(Active Magnetic Bearing AMB)시스템의 제어를 위한 새로운 퍼지제어 알고리즘을 제안한다. 이 방법은 AMB 시스템의 비선형 특성을 효과적으로 다루기 위하여 Joh등[4,5]이 제안한 LMI에 근거한 PDC 알고리즘과 퍼지 싱글톤을 사용하는 Mamdani형의 퍼지제어기를 복합한다. 이들은 각각 fine mode control과 coarse mode control이라고 구분하였다. coarse mode control은 회전축의 위치에러가 큰 경우 빠른 중심복귀 응답특성을 보이며 fine mode control은 회전축의 위치에러가 작을 때 요구되는 과도응답특성을 제공한다. 본 논에서 제안된 방법은 그성능을 입증하기 위하여 AMB 시스템의 제어에 적용되었으며 선형제어기와 일반적인 PDC 알고리즘으로 제어된 결과와의 비교를 통해 제안된 방법의 우수성을 보인다.