• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.424-427
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• 1995

In this paper, a control law based on the receding horizon concept which robustly stabilizes time-varying discrete linear systems, is proposed. A dynamic game problem minimizing the worst case performance, is adopted as an optimization problem which should be resolved at every current time. The objective of the proposed control law is to guarantee the closed loop stability and the infinite horizon $H^{\infty}$ norm bound. It is shown that the objective can be achieved by selecting the proper terminal weighting matrices which satisfy the inequality conditions proposed in this paper. An example is included to illustrate the results..

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.29-30
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• 2008

This paper defines a concept of "protectability" for the performance evaluation of distance relay considering its sensitivity and selectivity. The paper starts from the probabilistic modeling of the errors, and based on this model, a detailed explanation of protectability calculation for each zone of the distance relay is presented. An effect of the Weighting Rate and the Measurement Deviation on the protectability evaluation is also given. By considering this effect, the optimization of relay setting can be realized. The proposed method is applied to a typical model system to show its effectiveness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.625-631
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• 2002

A module design aims to develop product architecture that consists physically detachable units such as module. To develop the system of module design, this paper suggests the methodology of part grouping, evaluation of modularization of a product for improving modularization. To determine modules, module concept is proposed to satisfy the objectives of a modular design. Therefore, there are functional, structural, and process modularizations in a modular concept. Module grouping can be accomplished by using an optimization model that maximizes the sum of the weighting. The present study proposes the p-median model and the direct clustering technique. The optimal clustering solution can be obtained by comparing two clustering techniques. To find the best solution among part groups, evaluation of modularization is performed based on the concept of module design. For the evaluation of modularization, evaluation criteria of modularization are used in the matrix table.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.475-484
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• 2004

In this paper, we present a dynamic output-feedback receding horizon $H_{\infty}$controller for linear discrete-time systems with disturbance. The controller is obtained numerically from the finite horizon output-feedback $H_{\infty}$optimization problem, which is, in fact, hardly solved analytically. Under a matrix inequality condition on the terminal weighting matrix, the monotonic decreasing property of the cost is shown. This property guarantees both the closed-loop stability and the $H_{\infty}$norm bound. Then, we extend the proposed design method to a reference tracking problem and a problem for time-varying systems. Numerical examples are given to illustrate the performance of the proposed controller.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1100-1102
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• 1998

This paper presents the Two-Phase Neural Network(TPNN) to slove the Optimal Economic Environmental Dispatch problem of thermal generating units in electric power system. The TPNN, Compared with other Neural Networks, is very accurate and it takes smaller computer time for a optimization problem to converge. In this work, in order to provide useful information to the system operator, we are used the total environmental weight and relative weighting of individual insults(e.g., $SO_2$, $NO_X$ and $CO_2$) also, presented the simulation results of the dispatch changes according to the weights. The Two-Phase Neural Network is tested on a 11-unit 3-pollutant system to prove of effectiveness and applicability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.661-666
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• 2015

This paper proposes a method for solving running cost problem by minimizing switching reactive power compensation devices. An objective function was modeled by calculating the weighting value of cost, and a solution was derived using ILP. This paper suggests optimal coordinative control method between FACTS, Shunt Reactors, Capacitors and OLTC. Therefore, it is valuable for decision maker in determining order and capacity of devices which gaining a voltage stabilization. As a result, the objectives of voltage stabilization and cost minimization were achieved simultaneously. This realizes the economic efficiency of the system. We start by showing how to solve systems of linear equations using the language of pivots and tableaus. The effectiveness of this technique is demonstrated in modified PSS/E MIGUM 45 bus system. The simulation results show the effectiveness of this algorithm by comparing the outcome withseveral established methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.285-288
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• 2006

Most previous studies on improving the effectiveness of CBR have focused on the similarity function aspect or optimization of case features and their weights. However, according to some of the prior research, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. Nonetheless, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors that combine, as well as the weight of each feature. The new model is applied to the real-world case of a major telecommunication company in Korea in order to build the prediction model for the customer profitability level. Experimental results show that our GA-optimized CBR approach outperforms other AI techniques for this mulriclass classification problem.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.592-600
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• 2014

This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1163-1170
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• 2008

A mission scheduling optimization algorithm according to the purpose of satellite operations is developed using genetic algorithm. Satellite mission scheduling is making a timetable of missions which are slated to be performed. It is essential to make an optimized timetable considering related conditions and parameters for effective mission performance. Thus, as important criterions and parameters related to scheduling vary with the purpose of satellite operation, those factors should be fully considered and reflected when the satellite mission scheduling algorithm is developed. The developed algorithm in this study is implemented and verified through a comprehensive simulation study. As a result, it is shown that the algorithm can be applied into various type of the satellite mission operations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.969-978
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• 2008

In a linear cascade experimental apparatus, when it adopts only few blades as well as satisfies the periodic condition between blades, it gives several advantages in experiment. In this study, wall design on a cascade experimental apparatus is conducted to obtain the periodic condition on two blades installed within a passage of which the width is double pitch. The Mach number difference on the blade surface obtained with the periodic and wall condition is chosen as an objective function, and twelve design variables which are related to the wall shape are selected. A wall shape is designed using a gradient-based optimization method. Adjustment of range and weighting function are applied to calculate the objective function to avoid unrealistic evaluation of the objective function. By applying these methods, the computed results show same flow structures obtained with the periodic condition.