• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.639-645
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• 2005

GRID environments have been developed in distributed heterogeneous computing infrastructure for advanced science and engineering Therefore efficient scheduling algorithms for allocating user job to resources in the GRID environment are required. Many scheduling algorithms have been proposed, but these algorithms are not suitable for the GRID environment. That is the previous scheduling algorithm does not consider network bandwidth between multiple resources. In this paper, we propose a new scheduling algorithm for Global GRID environment and show that our algorithm has better performance than other scheduling algorithms through extensive simulation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1201-1210
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• 2000

In order to tolerate faults which may occur during the execution of distributed tasks in high-performance parallel computer systems, tasks are duplicated on different processors. In this paper, by utilizing the task duplication based scheduling algorithm, a new task scheduling algorithm which duplicates each task on more than two different processors with the minimum schedule length is presented, and the number of processors required for the duplication is analyzed with the ratio of communication cost to computation time and the workload of the system. A simulation with various task graphs reveals that the number of processors required for the full-duplex fault-tolerant task scheduling with the obtainable minimum schedule length increases about 30% to 75% when compared with that of the task duplication based scheduling algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.77-84
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• 2007

In this paper, Takagi-Sugeno (TS) fuzzy integral control is investigated to regulate the output voltage of an asymmetric half-bridge (AHB) DC/DC converter; First, we model the dynamic characteristics of the AHB DC/DC converter with state-space averaging method and small perturbation at an operating point. After introducing an additional integral state of the output regulation error, we obtain the $5^{th}$-order TS fuzzy model of the AHB DC/DC converter. Second, the concept of the parallel distributed compensation is applied to design the fuzzy integral controller, in which the state feedback gains are obtained by solving the linear matrix inequalities (LMIs). Finally, simulation results are presented to show the performance of the considered design method as the output voltage regulator and compared to the results for which the conventional loop gain method is used.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.16-18
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• 2001

Recently, a study on operation in parallel between Distributed Generation(DG) unit and power distribution system has been growing interest in power distribution system. But, introducing the DG unit causes the problem due to rising the voltage variation on power distribution system. So, This paper presents the effect of introducing DG unit on distribution system. For this simulation, KEPCO distribution system is used.

• Structural Engineering and Mechanics
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• v.43 no.2
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• pp.163-177
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• 2012

This paper presents a LMI(linear matrix inequality)-based fuzzy approach of modeling and active vibration control of geometrically nonlinear flexible plates with piezoelectric materials as actuators and sensors. The large-amplitude vibration characteristics and dynamic partial differential equation of a piezoelectric flexible rectangular thin plate structure are obtained by using generalized Fourier series and numerical integral. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the nonlinear structural system, which combines the fuzzy inference rule with the local linear state space model. A robust fuzzy dynamic output feedback control law based on the T-S fuzzy model is designed by the parallel distributed compensation (PDC) technique, and stability analysis and disturbance rejection problems are guaranteed by LMI method. The simulation result shows that the fuzzy dynamic output feedback controller based on a two-rule T-S fuzzy model performs well, and the vibration of plate structure with geometrical nonlinearity is suppressed, which is less complex in computation and can be practically implemented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.934-940
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• 1991

The multi-layer neural network that has broadly been utilized in designing the controller of robot manipulator possesses the desirable characteristics of learning capacity, by which the uncertain variation of the dynamic parameters of robot can be handled adaptively, and parallel distributed processing that makes it possible to control on real-time. However the error back propagation algorithm that has been utilized popularly in the learning of the multi-layer neural network has the problem of its slow convergencs speed. In this paper, an approach to improve the convergence speed is proposed using fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manipulator.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.138-140
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• 2018

Parallel distributed generators (DGs) in the islanded microgrid are generally operated autonomously by means of the droop control scheme. However, the traditional droop control methods which use the P-${\omega}$ and Q-E curve to share power between DGs are still concerned to improve the accuracy of reactive power sharing. Moreover, the uncontrolled harmonic power reduces the point of common coupling (PCC) voltage quality and microgrid stability. In order to solve these problems, this paper proposes an enhanced PCC harmonic control strategy and an improved reactive power sharing control scheme. Based on the low bandwidth communications, a secondary control is implemented with both central controller and local controller. The effectiveness of the proposed control scheme is analyzed through the simulation.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.184-190
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• 2005

The railway characteristic, which is concerned, as most utilities is unbalance produced by the large single-phase loads. Here are two theoretical concerns associated with unbalanced loads. First, generator rotor heating resulting from unbalanced current flow, Second, there is the possibility of motor overheating in industrial plants, due to the unbalanced voltage. Therefore, the exact assessment of the voltage unbalance must be carried out preferentially as well as load forecast at stages of designing and planning for the electric railway system. This paper proposes a new analysis model to more effectively estimate voltage unbalance. Numerous distributed circuits in the electric railway system are composed by components. The entire system can be easily modeled by the combination of four-port representation of each component in parallel and/or series. Simulation results using the model are compared with field data, and it verifies the accuracy of the proposed model.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.804-806
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• 1995

This paper discusses Self-organized Distributed Networks(SODN) as identifier of nonlinear dynamical systems. The structure of system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. The learning with the proposed SODN is fast and precise. Such properties arc caused from the local learning mechanism. Each local networks learns only data in a subregion. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the SODN. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems.