• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.34-39
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• 2013

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2475-2480
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• 2003

A control system design based on coupled nonlinear oscillators (CNOs) for a self-organized swarm system is presented. In this scheme, agents self-organize to flock and arrange group formations through attractive and repulsive forces among themselves using CNOs. Virtual agents are also used to create richer group formation patterns. The objective of the swarm control in this paper is to follow a moving target with a final group formation in the shortest possible time despite some obstacles. The simulation results have shown that the proposed scheme can effectively construct a self-organized multi-agent swarm system capable of group formation and group immigration despite the emergence of obstacles.

• Knowledge Management Research
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• v.9 no.3
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• pp.159-172
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• 2008

기업의 지적자산을 효과적으로 관리하는 지식경영 차원에서 기업들은 디지털 시대에 부합되도록 다양한 종류의 지식을 창조해내는 디지털 창의성을 기반으로 한 지식 경쟁력 향상 방안을 요구하고 있다. 이에 본 연구에서는 디지털창의성의 개념을 정의하고 이들에게 영향을 미치는 구성요인으로 디지털환경, 전문성영역, 디지털리스트성향을 제시하고 구성원의 다양성에 따른 디지털 창의성 변화와 경영성과에 미치는 영향을 다중 에이전트 시뮬레이션 접근방법을 사용하여 분석 하였다. 분석결과 구성원의 다양성이 높은 집단일 경우 시간의 흐름에 따라 구성원의 다양성이 낮은 집단, 즉 동질성이 높은 집단 보다 지식관리시스템 (KMS)을 이용한 지식의 생성 및 공유와 디지털창의성에 영향을 주는 강도가 높은 것으로 나타났다. 또한, 전문성영역, 디지털리스트성향이 디지털 창의성에 유의한 영향을 미치며, 디지털 창의성도 경영성과에 유의한 영향을 미치는 것으로 나타났다. 이러한 결과를 바탕으로 디지털 창의성과 경영성과 향상에 대한 시사점 및 향후 연구방향을 제시하였다.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.408-413
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• 2007

최근 인구와 기계문명의 발달로 예전에 비해 좀더 복잡한 응급 사고가 발생하고 있다. 현재 응급 구조 시스템은 타인에 의한 신고나 정적인 웹페이지로 수집된 정보를 통해 당시 상황에 맞춰 응급 체계를 수립하고 있다. 이는 비전문 의료인인 구급대원의 현장 판단과 의료기관으로의 부적절한 판단으로 인해 응급 환자의 적절한 치료의 가능성을 낮추는 요인이 될 수 있다. 따라서 선행연구로써 기존의 응급 의료 시스템에 멀티 에이전트 개념을 도입하여 멀티 에이전트 기반의 응급 의료 시스템(MAEMS)을 모델링하였다. 멀티 에이전트 시스템은 독립적인 성격과 자율적인 성격으로 않은 부분에 응용되어 설계되고 있다. 특히 에이전트의 독립적인 성격은 이질적인 환경에서 동일한 목적의 행위를 수행할 수 있으며, 동적으로 많은 변화가 있는 상황에서 자율적으로 판단하여 행동할 수 있다. 본 논문에서는 MAEMS에 구성되어 있는 각 에이전트를 구현하며, ARENA를 통해 시뮬레이션함으로써 실제 통계자료와 비교하여 멀티 에이전트를 도입한 응급 의료 시스템의 효율성에 대해 연구한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.538-541
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• 2010

상황인지 시뮬레이션이란 상황자료의 수집, 추론 및 결론 도출의 과정을 실제 환경이 아닌 가상의 시뮬레이션 환경 안에서 실험해 볼 수 있는 것을 말하며, 상황인지 기술과 DEVS(Discrete Event System Specification), 페트리-넷(Petri-Net)등의 기반 기술이 사용된다. 본 논문에서는 사용자들이 보다 편리하게 상황인지 시스템을 구축하고 실제보다 적은 시간으로 구축된 시스템을 실험할 수 있는 시뮬레이션 환경을 제공할 수 있는 통합 개발 프레임워크를 개발하고자 한다. 시뮬레이션 통합 개발 프레임워크 특징으로는, 첫째 상황인지를 위한 추론 기능을 가지는 에이전트와 시뮬레이션 기능들을 플러그인 및 라이브러리로 제공할 수 있고, 둘째, 통합환경 안에서 제공되는 도구들을 사용하여 사용자들이 보다 편리하게 개발 및 실험을 할 수 있다는 장점이 있다. 따라서 본 논문에서는 상황 아키텍처를 위한 모델 표현 계층, 멀티 에이전트 시스템을 위한 연산 계층, 환경과의 상호작용을 위한 인터랙션 계층, 그리고 시뮬레이션 계층인 4-계층구조의 통합개발환경을 연구하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.355-362
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• 2009

In this paper, we present a framework for managing group behaviors in multi-agent swarm systems. The framework explores the benefits by dynamic associations with the proposed artificial potential functions to realize complex swarming behaviors. A key development is the introduction of a set of flocking by dynamic association (DA) algorithms that effectively deal with a host of swarming issues such as cooperation for fast migration to a target, flexible and agile formation, and inter-agent collision avoidance. In particular, the DA algorithms employ a so-called systematic singular association (SSA) rule for fast migration to a target and compact formation through inter-agent interaction. The resulting algorithms enjoy two important interrelated benefits. First, the SSA rule greatly reduces time-consuming for migration and satisfies low possibility that agents may be lost. Secondly, the SSA is advantageous for practical implementations, since it considers for agents even the case that a target is blocked by obstacles. Extensive simulation presents to illustrate the viability and effectiveness of the proposed framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2895-2921
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• 2018

Security has become one of the major concerns in mobile adhoc networks (MANETs). Data and voice communication amongst roaming battlefield entities (such as platoon of soldiers, inter-battlefield tanks and military aircrafts) served by MANETs throw several challenges. It requires complex securing strategy to address threats such as unauthorized network access, man in the middle attacks, denial of service etc., to provide highly reliable communication amongst the nodes. Intrusion Detection and Prevention System (IDPS) undoubtedly is a crucial ingredient to address these threats. IDPS in MANET is managed by Command Control Communication and Intelligence (C3I) system. It consists of networked computers in the tactical battle area that facilitates comprehensive situation awareness by the commanders for timely and optimum decision-making. Key issue in such IDPS mechanism is lack of Smart Learning Engine. We propose a novel behavioral based "Smart Multi-Instance Multi-Label Intrusion Detection and Prevention System (MIML-IDPS)" that follows a distributed and centralized architecture to support a Robust C3I System. This protocol is deployed in a virtually clustered non-uniform network topology with dynamic election of several virtual head nodes acting as a client Intrusion Detection agent connected to a centralized server IDPS located at Command and Control Center. Distributed virtual client nodes serve as the intelligent decision processing unit and centralized IDPS server act as a Smart MIML decision making unit. Simulation and experimental analysis shows the proposed protocol exhibits computational intelligence with counter attacks, efficient memory utilization, classification accuracy and decision convergence in securing C3I System in a Tactical Battlefield environment.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.226-234
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• 2022

With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.