• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1231-1237
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• 2014

This paper proposes a reduced-order disturbance observer based coordinated tracking controller for uncertain heterogeneous multi-agent systems. To this end, first the control problem is converted as a robust control problem. Then, a dynamic coordinated controller is designed based on the recently proposed reduced-order disturbance observer. Simulation results are given to show the effectiveness of the proposed control scheme.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.164-172
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• 2023

Sharing power data between electrical power grids is crucial in energy management. The multi-agent approach has been applied in various applications to improve the development of complex systems by making them both independent and collaborative. The smart grid is one of the most intricate systems that requires a higher level of independence, reliability, protection, and adaptability to user requests. In this paper, a multi-agent system is utilized to share knowledge and tackle challenges in smart grids. The shared information is used to make decisions that aid in power distribution management within the grid and with other networks. The proposed multi-agent mechanism improves the reliability of the power system by providing the necessary information at critical times. The results indicate that the multi-agent system operates efficiently and promptly, making it a highly promising candidate for smart grid management.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.507-512
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• 1998

It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7451-7458
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• 2014

In this paper, the system modeling and multi-agent control algorithm in isolated wind hybrid power systems are proposed. The multi-agent control is a new type of the hybrid control method that is made up of wind turbine, diesel generator, battery, and dumpload. Fourteen different modes of operations of the wind hybrid power system are performed by wind speed changes and the SOC of battery. Simulation results show that the efficient operations under various wind variations in isolated wind hybrid power systems can be obtained using proposed algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.792-812
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• 2022

Multi-agent systems often need to achieve the goal of learning more effectively for a task through coordination. Although the introduction of deep learning has addressed the state space problems, multi-agent learning remains infeasible because of the joint action spaces. Large-scale joint action spaces can be sparse according to implicit or explicit coordination structure, which can ensure reasonable coordination action through the coordination structure. In general, the multi-agent system is dynamic, which makes the relations among agents and the coordination structure are dynamic. Therefore, the explicit coordination structure can better represent the coordinative relationship among agents and achieve better coordination between agents. Inspired by the maximization of social group utility, we dynamically construct a factor graph as an explicit coordination structure to express the coordinative relationship according to the utility among agents and estimate the joint action values based on the local utility transfer among factor graphs. We present the application of such techniques in the scenario of multiple intelligent vehicle systems, where state space and action space are a problem and have too many interactions among agents. The results on the multiple intelligent vehicle systems demonstrate the efficiency and effectiveness of our proposed methods.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.37-46
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• 2012

The scheduling problem of large products like ships, airplanes, space shuttles, assembled constructions, and automobiles is very complex in nature. To reduce inherent computational complexity, we often design scheduling systems that the original problem is decomposed into small sub-problems, which are scheduled independently and integrated into the original one. Moreover, the steep growth of communication technology and logistics makes it possible to produce a lot of multi-nation corporation by which products are produced across more than one plant. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. In this research, we suggest an agent-based coordinating mechanism for multi-level scheduling systems in supply chain. For design of a general coordination mechanism, at first, we propose a grammar to define individual scheduling agents which are responsible to their own plants, and a meta-level coordination agent which is engaged to supervise individual scheduling agents. Second, we suggest scheduling agent communication protocols for each scheduling agent topology which is classified according to the system architecture, existence of coordinator, and direction of coordination. We also suggest a scheduling agent communication language which consists of three layers : Agent Communication Layer, Scheduling Coordination Layer, Industry-specific Layer. Finally, in order to improve the efficiency of communication among scheduling agents we suggest a rough capacity coordination model which supports to monitor participating agents and analyze the status of them. With this coordination mechanism, we can easily model coordination processes of multiple scheduling systems. In the future, we will apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly-plant-scheduling agents, and a meta-level coordination agent. A series of experiment using the real-world data will be performed to examine this mechanism.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.275-278
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• 2006

멀티 에이전트(Multi-Agent)들이 상호 연동하여 공통의 목적을 수행하기 위해서는 에이전트를 관리하는 매니지먼트 에이전트(Management Agent)가 요구되고, 주어진 환경에서 획득한 제한된 지식을 효율적으로 이용하는 방법이 필요하다. 본 논문에서는 네이브 베이즈 이론을 적용하여 각 에이전트의 속성값(Attribute Value)에 따라 매니지먼트 에이전트가 각 에이전트를 효율적으로 관리할 수 있는 NBMA(Naive Bayes Management Agent)를 제안하고 이를 이용한 미팅 참가 결정 에이전트를 제안한다. NBMA는 고유한 속성을 지닌 여러 개의 하위 에이전트와 그들을 관리하는 매니지먼트 에이전트로 구성되어 있으며 매니지먼트 에이전트는 하위 에이전트들의 고유한 속성에 대한 메타지식을 이용하여 관리 하도록 한다. 하위 에이전트간에는 상호 조건부 독립(mutually conditional independence) 가정하에 복수의 속성값을 취하며 이러한 속성값에 따라 매니지먼트 에이전트가 조정과 의사결정을 하도록 한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.660-668
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• 2007

In order to improve the efficiency of service restoration function in the current Distribution Automation System (DAS), in this paper it is proposed a more advanced and efficient service restoration approach using Multi-Agent technique based on distributed networks. In the current DAS, communication networks or protocol structures are centralized with communications between the central station and FRTU through 1:1 connection. In order to maintain the current systems and enhance the proposed Multi-Agent based service restoration scheme, a device of communication and intelligence, named MASX, is newly developed to make a FRTU as an agent to cooperate each others. the proposed system applied in a demo system for an distribution automation system and shows 8 times reduction of restoration time in restoration of blackouts.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.147-152
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• 1999

It is an interesting area in the field of artifical intelligence to find an analytic model of cooperative structure for multiagent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent agents solving a pursuit problem in a continuous world. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to find the fuzzy logic controller seems to be promising.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.439-444
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• 2012

In this study, we address the formation control problem of coupled unicycle-type mobile robots, each of which can interact with its neighboring robots by communicating their position outputs. Each communication link between two mobile robots is assumed to be established according to the given time-varying interconnection topology that switches within a finite set of connected fixed undirected networks and has a non-vanishing dwell time. Under this setup, we propose a distributed formation control algorithm by using the dynamics extension and feedback linearization methods, and by employing a consensus algorithm for linear multi-agent systems which provides arbitrary fast convergence rate to the agreement of the multi-agent system. Finally, the proposed result is demonstrated through a computer simulation.