• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2376-2394
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• 2013

In order to ensure both of the whole system capacity and users QoS requirements in heterogeneous wireless networks, admission control mechanism should be well designed. In this paper, Multi-agent Q-learning based Admission Control Mechanism (MQACM) is proposed to handle new and handoff call access problems appropriately. MQACM obtains the optimal decision policy by using an improved form of single-agent Q-learning method, Multi-agent Q-learning (MQ) method. MQ method is creatively introduced to solve the admission control problem in heterogeneous wireless networks in this paper. In addition, different priorities are allocated to multiple services aiming to make MQACM perform even well in congested network scenarios. It can be observed from both analysis and simulation results that our proposed method not only outperforms existing schemes with enhanced call blocking probability and handoff dropping probability performance, but also has better network universality and stability than other schemes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.10
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• pp.35-43
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• 2012

In this paper, a development of agent-based IEDs(Intelligent electronic devices) for integration control of building microgrid in smart green building are proposed. To manage and control this complex energy system of smart green buildings, multi-agent system based networks is needed. Thus, several IEDs for utilizing multi-agent system are developed and modified for the their verification of performance as agent modules functions in the integrated experimental equipment. The good performance of these IED agents are verified from experimental results obtained from seamless bi-directional communication by SOAP/XML protocol between PC agent and IED agent.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.937-944
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• 2003

The most important problems in the multi-agent system are to accomplish a gnat through the efficient coordination of several agents and to prevent collision with other agents. In this paper, we propose a new control strategy for succeeding the goal of a prey pursuit problem efficiently Our control method uses reinforcement learning to control the multi-agent system and consider the distance as well as the space relationship among the agents in the state space of the prey pursuit problem.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1225-1230
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• 2014

This paper investigates the group average-consensus and group formation-consensus problems for first-order multi-agent systems. The control protocol for group consensus is designed by considering the positive adjacency elements. Since each intra-group Laplacian matrix cannot be satisfied with the in-degree balance because of the positive adjacency elements between groups, we decompose the Laplacian matrix into an intra-group Laplacian matrix and an inter-group Laplacian matrix. Moreover, average matrices are used in the control protocol to analyze the stability of multi-agent systems with a fixed and undirected communication topology. Using the graph theory and the Lyapunov functional, stability analysis is performed for group average-consensus and group formation-consensus, respectively. Finally, some simulation results are presented to validate the effectiveness of the proposed control protocol for group consensus.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.526-532
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• 2014

In this paper, we present and analyze a LQ (Linear Quadratic) inverse optimal state-consensus protocol for continuous-time multi-agent systems with undirected graph topology. By Lyapunov analysis of the state-consensus error dynamics, we show the sufficient conditions on the algebraic connectivity of the graph to guarantee LQ inverse optimality and closed-loop stability. A more relaxed stability condition is also provided in terms of the algebraic connectivity. Finally, a formation control protocol for multiple mobile robots is proposed based on the target LQ inverse optimal consensus protocol, and the simulation results are provided to verify the performance of the proposed LQ inverse formation control method.

• 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.

• 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 Automotive Technology
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• v.7 no.1
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• pp.25-34
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• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.187-193
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• 2013

In multi-agent systems, How to coordinate the behaviors of the agents through learning is a very important problem. The most important problems in the multi-agent system are to accomplish a goal through the efficient coordination of several agents and to prevent collision with other agents. In this paper, we propose a novel approach by using hybrid learning strategy. It is used hybrid learning strategy to control the multi-agent system efficiently by using the spatial relationship among the agents. Through experiments, we can see approximate faster the goal then other strategies and avoids collision among the agents.