• Journal of IKEEE
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• v.23 no.2
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• pp.716-721
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• 2019

A novel switching differentiator-based backstepping controller for uncertain pure-feedback nonlinear systems is proposed. Using asymptotically convergent switching differentiator, time-derivatives of the virtual controls are directly estimated in every backstepping design steps. As a result, the control law has an extremely simple form and asymptotical stability of the tracking error is guaranteed regardless of parametric or unstructured uncertainties and unmatched disturbances in the considered system. It is required no universal approximators such as neural networks or fuzzy logic systems that are adaptively tuned online to cope with system uncertainties. Simulation results show the simplicity and performance of the proposed controller.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.281-292
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• 2019

This paper proposed a new technology to control a path forging parts in limited narrow space of manufacturing process automation for smart factory. In the motion control, we adapted the obstacle avoidance technology based on ultrasonic sensors. The new motion control performance test for a mobile robot is experimented in narrow space environments. The travelling path control is performed by a fuzzy control logic. which plays a role for selecting an appropriate behavior in accordance with the situation in the vicinity of the mobile robot. Ultrasonic sensors installed at the front face of the mobile robot are used. In order to update the current position and heading angle of the mobile robot, a new approch is adapted. The reliability is illustrated by simulation and experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.4
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• pp.297-304
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• 2022

This study compares the performance of artificial intelligence (AI)-based maximum power point tracking (MPPT) methods under partial shading conditions in a photovoltaic generation system. Although many studies on AI-based MPPT have been conducted, few studies comparing the tracking performance of various AI-based global MPPT methods seem to exist in the literature. Therefore, this study compares four representative AI-based global MPPT methods including fuzzy logic control (FLC), particle swarm optimization (PSO), grey wolf optimization (GWO), and genetic algorithm (GA). Each method is theoretically analyzed in detail and compared through simulation studies with MATLAB/Simulink under the same conditions. Based on the results of performance comparison, PSO, GWO, and GA successfully tracked the global maximum power point. In particular, the tracking speed of GA was the fastest among the investigated methods under the given conditions.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.633-645
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• 2022

The active tuned mass damper (ATMD) is an efficient and reliable structural control system for mitigating the dynamic response of structures. The inertial force that an ATMD exerts on a structure to attenuate its otherwise large kinetic energy and undesirable vibrations and displacements is proportional to its excursion. Achieving a balance between the inertial force and excursion requires a control law or feedback mechanism. This study presents a technique for the optimum design of a sliding mode controller (SMC) as the control law for ATMD-equipped structures subjected to earthquakes. The technique includes optimizing an SMC under an artificial earthquake followed by testing its performance under real earthquakes. The SMC of a real 11-story shear building is optimized to demonstrate the technique, and its performance in mitigating the displacements of the building under benchmark near- and far-fault earthquakes is compared against that of a few other techniques (proportional-integral-derivative [PID], linear-quadratic regulator [LQR], and fuzzy logic control [FLC]). Results indicate that the optimum SMC outperforms PID and LQR and exhibits performance comparable to that of FLC in reducing displacements.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.710-713
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• 2008

센서 네트워크는 습도, 온도, 조도 등의 다양한 정보를 수집할 수 있는 센서들을 특정한 지역이나 광범위한 지역에 분포하여 특정 이벤트를 탐지하거나 계속적으로 환경을 관찰하여 수집된 정보를 효율적으로 Base Station으로 전송하는 일종의 애드 혹 네트워크이다. 본 논문은 센서 네트워크의 라우팅 프로토콜 중 PEGASIS와 동심원 형태의 클러스터링 방법에 대해 취약점을 알아보고, 이를 해결하기 위한 방법으로 클러스터 헤드 선출을 위한 두 가지 기준을 정하고, 퍼지 이론을 기반으로 적절한 선택 값을 도출하여 효율적인 클러스터 헤드를 선출하는 방법을 제안한다. 이 방법은 각 센서 노드들의 남아있는 에너지를 고려할 수 있으며, 각 레벨에서 클러스터 헤드들은 가깝게 위치하게 되어 Multi-hop으로 데이터 전송 시 기존의 방법들보다 전송 거리를 줄일 수 있는 장점을 가지고 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.936-940
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• 2007

본 논문은 무선 센서 네트워크의 에너지 효율적인 운영을 위해 무선 센서 네트워크 환경에 적합한 클러스터 헤드 선출 메커니즘을 제안한다. LEACH 와 같은 기존의 확률 모델 기반의 클러스터 헤드 선출 메커니즘들은 각 라운드마다 클러스터 헤드로 선출될 확률과 라운드 횟수 등을 바탕으로 클러스터 헤드를 선출한다. 그러나 이와 같은 방법은 각 노드의 상황을 고려하지 않아 네트워크의 수명을 단축시킬 수 있다. 이러한 문제점을 해결하기 위해서는 각 센서 노드의 에너지 및 노드 분포 상황을 고려하여 클러스터 헤드를 선출해야 한다. 하지만 실제 무선 센서 네트워크 환경에서는 클러스터 헤드 선출을 위해 정확한 정보를 수집하고 이를 계산하는데 있어 큰 오버헤드가 발생하는 문제점이 있다. 이에 본 논문에서는 정보 수집 및 계산에 있어서 오버헤드를 줄이고 네트워크의 수명을 극대화하기 위하여 퍼지 논리를 이용한 퍼지 논리 기반의 클러스터 헤드 선출 메커니즘을 제안한다. Matlab 을 통한 시뮬레이션 결과 LEACH 에 비해 퍼지 논리 기반의 클러스터 헤드 선출 메커니즘을 이용했을 경우 네트워크 수명이 약 16.3% 향상되었다.

• Journal of the Korea Society for Simulation
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• v.20 no.1
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• pp.69-77
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• 2011

Modeling and Simulation(M&S) technology gets an attention from various parts such as industry and military. Especially, military uses the technology to cope with a different situation from the one in the Cold War and maximize the effect of training against the cost in the new environment. In order for the training based on M&S technology to be effective, the situations of a battlefield and a combat must be more realistically simulated. For this, a technique development on Computer-Generated Forces(CGF) which represents a unit's simulation logic and a human's simulated behaviors is focused. The CGF simulating a human's behaviors can be used in representing an enemy force, experimenting behaviors in a future war, and developing a new combat idea. This paper describes a methodology to accomplish Computer-Generated Forces' autonomous intelligence. It explains the process of applying a task behavior list based on the METT+T element onto CGFs. On the other hand, in the domain knowledge of military field manual, fuzzy facts such as "fast" and "sufficient" whose real values should be decided by domain experts can be easily found. In order to efficiently implement military simulation logics involved with such subjectivity, using a fuzzy inference methodology can be effective. In this study, a fuzzy inference methodology is also applied.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.18-35
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• 1993

The water level control system of the steam generator in a pressurized water reactor and its control problems are analysed. In this work the stable control strategy during the low power operation and transient states is studied. To solve the problem, a fuzzy logic control method is applied as a basic algorithm of the controller. The control algorithm is based on the operator's knowledges and the experiences of manual operation for water level control at the compact nuclear simulator set up in Korea Atomic Energy Research Institute. From a viewpoint of the system realization, the control variables and rules are established considering simpler tuning and the input-output relation. The control strategy includes the dynamic tuning method and employs a substitutional information using the bypass valve opening instead of incorrectly measured signal at the low flow rate as the fuzzy variable of the flow rate during the pressure control mode of the steam generator. It also involves the switching algorithm between the control valves to suppress the perturbation of water level. The simulation results show that both of the fine control action at the small level error and the quick response at the large level error can be obtained and that the performance of the controller is improved.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.69-78
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• 2011

A large-scale sensor network usually operates in open and unattended environments, hence individual sensor node is vulnerable to various attacks. Therefore, malicious attackers can physically capture sensor nodes and inject false reports into the network easily through compromised nodes. These false reports are forwarded to the base station. The false report injection attack causes not only false alarms, but also the depletion of the restricted energy resources in a battery powered network. The statistical en-route filtering (SEF) mechanism was proposed to detect and drop false reports en route. In SEF, the choice of routing paths largely affect the energy consumption rate and the detecting power of the false report. To sustain the secure routing path, when and how to execute the path re-selection is greatly need by reason of the frequent network topology change and the nodes's limitations. In this paper, the regional path re-selection period determination method is proposed for efficient usage of the limited energy resource. A fuzzy logic system is exploited in order to dynamically determine the path re-selection period and compose the routing path. The simulation results show that up to 50% of the energy is saved by applying the proposed method.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.4
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• pp.109-120
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• 2016

This study aims to assess vulnerability in urban thermal environments of Seoul by using indicators frequently used in previous studies as well as effective indicators for spatial planning like urban and environmental planning. For this purpose, fifteen indicators that influence urban thermal environments such as heat waves, urban heat island effects, and urban micro-climates were identified based on literature reviews. Indicators for presenting urban structure and spatial properties were included; for example, building volume as 'exposure to climate', buildings completed before 1980 as 'sensitivity', and green space areas as 'adaptive capacity'. Among them, twelve indicators were applied to assess vulnerability in urban thermal environments of Seoul by using a GIS spatial analysis combined with fuzzy logic. The results show that the Gangnam area is identified as more vulnerable to a heat environment as compared to the Gangbuk area. In the Gangnam area, Seocho-gu, Gangnam-gu, Dongjak-gu, Yeongdeungpo-gu, Gangseo-gu were relatively high in vulnerability, while Dongdaemun-gu, Gangbuk-gu, Gwangjin-gu, Jungrang-gu were relatively high in the Gangbuk area. Gwanak-gu, Dobong-gu, Eunpyeong-gu, and Nowon-gu, which include forested areas, have low vulnerability in the sectors of 'exposure to climate' and 'sensitivity' due to the impact of Gwanaksan and Bukhansan. However, some areas with high vulnerability like Seocho-gu and Gangnam-gu may have lower vulnerability if the indicator 'status of air conditioning' from the sector of 'adaptive capacity' is used. This study could support the establishment of a practicable thermal environment policy and spatial planning to reduce heat-related risks in the field of urban and environmental planning.