• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.108-113
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• 2005

This paper suggests a control method for an efficient topology/parameter evolution in a bond graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynamic systems. We adopt a hierarchical breeding control mechanism with fitness-level-dependent differences to obtain better balancing of topology/parameter search - biased toward topological changes at low fitness levels, and toward parameter changes at high fitness levels. As a testbed for this approach in bond graph synthesis, an eigenvalue assignment problem, which is to find bond graph models exhibiting minimal distance errors from target sets of eigenvalues, was tested and showed improved performance for various sets of eigenvalues.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1600-1604
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• 2010

This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

• Journal of Korean Society for Quality Management
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• v.29 no.4
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• pp.82-91
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• 2001

Taguchi robust design is widely used to quality improve methods. Especially, interest of dynamic characteristics parameter design is getting grow. In this paper, we have a comparative analyzed three Signal-to-Noise Ratios which are used in American Supplier Institute(ASI), MINITAB and Taguchi series published by Japanese Standard Institute with numerical examples.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.211-214
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• 2005

This research studied robust design of composite structure under combined loading of bending and torsion. DOE (Design of Experiment) technique was used to find important design factors. The results show that the beam height, beam width, layer thickness and stack angle of outer-layer are important design parameter. The $2^{nd}$ DOE and RSM (Response Surface Model) were conducted to obtain optimum design. Multi-island genetic algorithm was used to optimum design. An approximate value of 6.65 mm in deflection was expected under optimum condition. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the sigma level reliability, the standard deviation of design parameter should be controlled within 2.5 % of average design value.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.829-835
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• 2009

Parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. However, there are difficulties in practical application, such as complexity and nonlinear relationships among quality characteristics and control factors (design factors), and interactions occurred among control factors. Neural networks have a learning capability and model free characteristics. There characteristics support neural networks as a competitive tool in processing multivariable input-output implementation. In this paper we propose a substantially simpler optimization procedure for parameter design using neural network. An example is illustrated to compare the difference between the Taguchi method and neural network method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.873-879
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• 2010

It is common to predict structural dynamic design parameters due to the change of design parameter, but to predict the amount of changed design parameter where the mass and stiffness are being modified are rarely found in previous literature. In this study, the changed design parameter in a proportional damping system is predicted by using sensitivity coefficients and an iterative method. The sensitivity coefficients are determined from the changes in eigenvectors; these changes are due to modification. This method is applied to a three-story shear structure. To validate the prediction of the changed design parameter, the results are compared to the reanalysis results; both results are in good agreement.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.138-141
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• 2008

The effects of design parameters for small scale hydro power(SSHP) plants due to rainfall condition have been studied. The model to predict hydrologic performance for SSHP plants is used in this study. The results from analysis for rainfall conditions based on Weibull distribution show that the capacity and load factor of SSHP site had large difference between the variation of shape and scale parameter. Especially, the hydrologic performance of SSHP site due to variation of shape parameter varied more sensitive than the case of variation of scale parameter. And also, the methodology represented in this study can be used to decide the primary design specifications of SSHP sites.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Journal of the Korean Solar Energy Society
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• v.28 no.1
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• pp.43-49
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• 2008

The effects of design parameters for small scale hydro power(SSHP) plants due to rainfall condition have been studied. The model to predict hydrologic performance for SSHP plants is used in this study. The results from analysis for rainfall conditions based on Weibull distribution show that the capacity and load factor of SSHP site had large difference between the variation of shape and scale parameter. Especially, the hydrologic performance of SSHP site due to variation of shape parameter varied more sensitive than the case of variation of scale parameter. And also, the methodology represented in this study can be used to decide the primary design specifications of SSHP sites.

• 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.