• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.223-226
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• 1998

The control objective of steam generator water level in the secondary circuit of a nuclear power plant is to regulate the water level at the desired set point. The dynamics of steam generators is non-linear in nature. The task of modelling such plant is very difficult and especially so when plant operating conditions change frequently. In these reasons, conventional PI gains over all pover range will not work efficiently and a manual control is generally used in low power operation. Therefore the robust H$\infty$ controller design method should be required. In this paper, we design the robust H$\infty$ controller for water level control of steam generator using a mixed H$\infty$ optimization with model-matching method. Firstly we choose the desired model that has good disturbance rejection performance. Secondly we design a stabilizing controller to keep the model-matching error small and also provide sufficiently large stability margin against additive perturbations of the nominal plant.

• East Asian mathematical journal
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• v.24 no.1
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• pp.21-25
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• 2008

The semilocal convergence of the secant method under $H{\ddot{o}}lder$ continuous divided differences in a Banach space setting for solving nonlinear equations has been examined by us in [3]. The local convergence was recently examined in [4]. Motivated by optimization considerations and using the same hypotheses but more precise estimates than in [4] we provide a local convergence analysis with the following advantages: larger radius of convergence and finer error estimates on the distances involved. The results can be used for projection methods, to develop the cheapest possible mesh refinement strategies and to solve equations involving autonomous differential equations [1], [4], [7], [8].

• Korean Journal of Computational Design and Engineering
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• v.9 no.3
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• pp.266-275
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• 2004

In this paper, a method for generating the planar developments of three-dimensional shoe upper surfaces is proposed. This method is based on the optimization technique minimizing the geometric error occurred on the developed planar surface. Additionally, a rapid mapping algorithm to transform a curve on flattened plane to original surface (or vice versa) is proposed. These techniques are implemented on the 2D/3D integrated shoe design system. Using this system, a prototype running shoe can be designed more precisely and can be manufactured more quickly.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.65-71
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• 1997

In this paper, we propose a new .mu.-controller design method using an equivalent weighting function $W_{\mu}$(s). The proposed mehtod is not guaranteed to converge to the minimum as D-K and .mu.-K iteration method. However, the robust performance problem can be converted into an equivalent $H^{\infty}$ optimization problem of unstructured uncertainty by using an equivalent weightng function $W_{\mu}$(s). Also we can find a .mu.-optimal controller iteratively using an error index $d_{\epsilon}$ of differnce between maximum singular value and .mu.-norm. And under the condition of the same order of scaling functions, the proposed method provides the .mu.-optimal controller with the degree less than that obtained by D-K iteration..

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.783-786
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• 2000

For the development of a ultra-precision CMC polishing system including on-machine measurement system, we study a corrective polishing algorithm. We calculated unit removal profiles for various polishing tools and polishing tool positions. Using these results we simulate the corrective polishing process based on dwell time control. We calculate dwell time distributions and residual error of the polishing simulation method and the FFT calculation method. We got good dwell time distributions and small residual when we used the FFT calculation method. This results will be used for the optimization of corrective polishing process.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.544-551
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• 2020

Reactor control is a standout amongst the most vital issues in the nuclear power plant. In this paper, the optimal design of variable structure controller (VSC) based on the lightning search algorithm (LSA) is proposed for a nuclear reactor power system. The LSA is a new optimization algorithm. It is used to find the optimal parameters of the VSC instead of the trial and error method or experts of the designer. The proposed algorithm is used for the tuning of the feedback gains and the sliding equation gains of the VSC to prove a good performance. Furthermore, the parameters of the VSC are tuned by the genetic algorithm (GA). Simulation tests are carried out to verify the performance and robustness of the proposed LSA-based VSC compared with GA-based VSC. The results prove the high performance and the superiority of VSC based on LSA compared with VSC based on GA.

• Transactions of Materials Processing
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• v.22 no.2
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• pp.93-100
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• 2013

A tryout is a series of process optimization for robust stamping before transfer to the press shop. During tryout, the drawbead control, blank shape determination, binder surface modification, etc., are carried out mainly by a trial-and-error approach. As the level of difficulty of the stamping process increases, the formability becomes more sensitive to the contour of deformed shape, i.e. the blank shape. A digital tryout technique, which simulates a real tryout process, is proposed in this study for challenging stamping processes. Since digital tryout is carried out on a desktop, not in a press shop, a precise control of the deformed contour can be achieved if an optimal blank design technique is utilized. In this work, the proposed digital tryout technique is validated by successful applications to different automotive parts.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.951-959
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• 2014

Recently Hazelton and Turlach (2009) proposed a weighted kernel density estimator for the deconvolution problem. In the case of Gaussian kernels and measurement error, they argued that the weighted kernel density estimator is a competitive estimator over the classical deconvolution kernel estimator. In this paper we consider weighted kernel density estimators when sample observations are contaminated by double exponentially distributed errors. The performance of the weighted kernel density estimators is compared over the classical deconvolution kernel estimator and the kernel density estimator based on the support vector regression method by means of a simulation study. The weighted density estimator with the Gaussian kernel shows numerical instability in practical implementation of optimization function. However the weighted density estimates with the double exponential kernel has very similar patterns to the classical kernel density estimates in the simulations, but the shape is less satisfactory than the classical kernel density estimator with the Gaussian kernel.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.523-527
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• 2004

This paper presents a new design methods of the short-term load forecasting system (STLFS) using the data mining. The proposed predictor takes form of the convex combination of the linear time series predictors for each inputs. The problem of estimating the consequent parameters is formulated by the convex optimization problem, which is to minimize the norm distance between the real load and the output of the linear time series estimator, The problem of estimating the premise parameters is to find the parameter value minimizing the error between the real load and the overall output. Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).