• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1347-1353
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• 2011

While most of the existing protection schemes have been designed with local information around individual components, these local schemes are not considered capable of protecting the modern electric power gird with growing complexity. Recent blackouts in North America and Europe have renewed the emphasis on coordinated protection and control actions to avoid systemwide blackouts, utilizing all of the available grid information. Thus, this paper proposes a new methodology, Agent-based Colored Petri Net (ACPN) modeling for systematically representing, modeling and analyzing information flows and interactions among the entities of the electric power grid. The paper demonstrates its efficacy and accuracy by investigating an ACPN model of a wide area protection system for a typical power grid. The proposed modeling and analysis schemes may further provide a framework to help assure reliability and interoperability of diverse smart grid components.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1371-1373
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• 2005

Nowadays, Intelligent Electronic Devices(IED) are widely used in power system. In order to improve the selectivity, sensitivity, and reliability of the power system composed by IEDs, A new fault tolerant IED system based on agent technique is presented in this paper. in the presented system, different with existing IED systems, the redundancies are drawn out from IED devices, and compose a standby backup system. And those redundancies are not specified to a particular type of IEDs. By using the agent technique, redundancies can download agents to modify their functions to fit different types of IEDs. As a conclusion, the reliability of the presented system is estimated in this paper.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.10a
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• pp.215-222
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• 2004

We synthesized a aziridine bonding agent that play an important role in increasing the adhesion property between polymer binders and solid particles. It increases the physical properties of polymer-based propellant. Chemical reaction between two materials increase the interface adhesion. We analyzed and studied the chemical characteristics of the material and physical properties of a liner applied the aziridine bonding agent. We also studied the adhesion property of a liner/propellant applied the aziridine bonding agent. 3M was use as control group. In accordance with US MIS (Missile Interim Specification) we examined the chemical properties. As a result of our study, newly synthesized aziridine bonding agent was as good as quality of 3M HX-868.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.293-298
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• 2004

To satisfy the requirements for QoS and acceptance ratio of the users using multimedia content service, it is required to control mechanism for QoS assurance and allocation of the stream server' resources based on CoS(Class of Service). To compare performance of the algorithm, we have classified the user by two classes (super class, base class) and control the acceptance ratio of user's requests by user's class information. We have experimented the test of network resources and test of processing time under server/client environment and agent environment. MA-URFA based on agent increases the acceptance ratio of super class and utilization ratio of network resources.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.390-397
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• 2013

This paper presents a consensus algorithm for uMAS (uncertain Multi-Agent Systems). Unlike previous results in which only nominal models for agents are considered, it is assumed that the uncertain agent model belongs to a known polytope set. In the middle of deriving the proposed algorithm, a convex set is found which includes all uncertainties in the problem using convexity of the polytope set. This set plays an important role in designing the consensus algorithm for uMAS. Based on the set, a consensus condition for uMAS is proposed and the corresponding consensus design problem is solved using LMI (Linear Matrix Inequality). Simulation result shows that the proposed consensus algorithm successfully leads to consensus of the state of uMAS.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3410-3419
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• 1999

Autonomous Intrusion Analysis Agent(AIAA) is Incident Response Team staff's tool that scans, analyses, reports and alerts the traces of intrusion based on system logs and intruder's backdoors inside compromised system by IR staff after security incident is reported to the IR team. AIAA is intelligent to recognize to check out who is intruder from all the user accounts and to report the suspected candidates to the master control system in IR team. IR staff who controls AIAA with master system can pick up an intruder from the candidates reported by AIAA agent and review all related summary reports and details including source host's mane, finger information, all illegal behavior and so on. AIAA is moved to compromised system by the staff to investigate the signature of intrusion along the trace of victim hosts and it is also operated in secret mode to detect the further intrusion. AIAA is alive in all victim systems until the incident is closed and IR staff can control AIAA operation and dialogue with AIAA agent in Web interface.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.84-92
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• 2006

Freeway Corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. Optimization results are verified by comparison with the results from MATDYMO.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.8-15
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• 2007

Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.

• Journal of the Korea Computer Graphics Society
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• v.30 no.1
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• pp.1-10
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• 2024

In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users' social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI's ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.164.1-164
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• 2001

Q-learning is a recent reinforcement learning algorithm that does not need a modeling of environment and it is a suitable approach to learn behaviors for autonomous agents. But when it is applied to multi-agent learning with many I/O states, it is usually too complex and slow. To overcome this problem in the multi-agent learning system, we propose the successive Q-learning algorithm. Successive Q-learning algorithm divides state-action pairs, which agents can have, into several Q-functions, so it can reduce complexity and calculation amounts. This algorithm is suitable for multi-agent learning in a dynamically changing environment. The proposed successive Q-learning algorithm is applied to the prey-predator problem with the one-prey and two-predators, and its effectiveness is verified from the efficient avoidance ability of the prey agent.