• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.62-65
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• 2004

An optimal robust controller design method for gun driving system is discussed in this paper. The parameters of the gun driving controller are tuned by using the LQR characteristics for the performance and robustness. Tuning method that optimize velocity error gives a significant improvement over the existing PID tuning methods. It is shown that the tuning result of real gun driving system which is regarded as rigidness model or stiffness model satisfy performance and robustness.

• International Journal of Advanced Culture Technology
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• v.1 no.2
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• pp.18-23
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• 2013

In this paper, we consider the problem of designing optimal sensing time and the minimization of energy consumption in the Cognitive radio Network. Trade-off between throughput and the sensing time are observed, and the equations are derived for the optimal choice of design variables. In this paper, we also look at the optimization problem involving all the design parameters together. The advantages of the proposed scheme for the spectrum sensing and access process are shown through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.168-173
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• 1987

The optimal Input design problem for linear system Which have the common parameters in the system and noise transfer functions. Exploiting the assumed Model structure and deriving the information matrix structure in detail, D-optimal open-loop stochastic input can be realized as an ARMA process under the Input or output variance constraints. In spite of the reduced order, It Is necessary to develop an efficient algorithms for the optimation with respect to the .rho..

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.909-913
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• 1998

Transient and static characteristics of HVDC inverter can be analyzed with various simulation tools. For the optimal filter design, various performance criteria are proposed. In this paper, performance index is calculated based on proposed per phase equivalent circuit. Voltage and harmonic and filter power loss are selected as criteria. Optimization procedure is performed to find optimal passive filter parameters. Dynamic characteristics is also analyzed with proposed equivalent circuit.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.40-45
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• 2008

This paper presents an optimal design of a permanent magnet actuator(PMA) using a parallel genetic algorithm. Dynamic characteristics of permanent magnet actuator model are analyzed by coupled electromagnetic-mechanical finite element method. Dynamic characteristics of PMA such as holding force, operating time, and peak current are obtained by no load test and compared with the analyzed results by coupled finite element method. The permanent magnet actuator model is optimized using a parallel genetic algorithm. Some design parameters of vertical length of permanent magnet, horizontal length of plunger, and depth of permanent magnet actuator are predefined for an optimal design of permanent magnet actuator model. Furthermore dynamic characteristics of the optimized permanent magnet actuator model are analyzed by coupled finite element method. A displacement of plunger, flowing current of the coil, force of plunger, and velocity of plunger of the optimized permanent magnet actuator model are compared with the results of a primary permanent magnet actuator model.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.6 no.1
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• pp.11-19
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• 1994

An optimal design for Gifford-McMahon/Joule-Thomson(GM-JT) refrigerators was performed by a numerical method. The design goal was to meet the cooling requirement for MRI systems, which was 3 Watt at 4 K. A general cycle analysis program was written to calculate the cooling capacity of the GM-JT refrigerators for the givenstage GM refrigerator. The program was executed for a specific refrigerator with various design parameters. The optimal values for the maximum cooling were found for the sizes of the heat exchangers, the mass flow rate of helium, and the compression pressure.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1938-1948
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• 2003

This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

• Earthquakes and Structures
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• v.1 no.3
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• pp.289-306
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• 2010

A gradient-based evolutionary optimization methodology is presented for finding the optimal design of viscous dampers to minimize an objective function defined for a linear multi-storey structure. The maximum value along height of the transfer function amplitudes for the interstorey drifts is taken as the objective function. Since the ground motion includes various uncertainties, the optimal damper placement may be different depending on the ground motion used for design. Furthermore, the transfer function treated as the objective function depends on the properties of structural parameters and added dampers. This implies that a more robust damper design is desired. A reliable and robust damping design system against any unpredictable ground motions can be provided by minimizing the maximum transfer function. Such design system is proposed in this paper.

• Journal of Power System Engineering
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• v.15 no.5
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• pp.72-76
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• 2011

In this work, the parameter optimization for thermal-sprayed Al/SiC composites have been designed by $L_9(3^4)$ orthogonal array and analysis of variance(ANOVA). Al/SiC composites were fabricated by flame spray process on steel substrate. The hardness of composites were measured using micro-vickers hardness tester, and these results were analyzed by ANOVA. The ANOVA results showed that the oxygen gas flow, powder feed rate and spray distance affect on the hardness of the Al/SiC composites. From the ANOVA results, the optimal combination of the flame spray parameters could be extracted. It was considered that experimental design using orthogonal array and ANOVA was efficient to determine optimal parameter of thermal-sprayed Al/SiC composites.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.