• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1204-1209
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• 1990

This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.

• Journal of Magnetics
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• v.17 no.1
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• pp.46-50
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• 2012

A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1943-1950
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• 2010

Superimposition of horizontal and vertical curves may hamper the ride comfort and the running stability of train and largely affect the maintenance cost. However, in many cases, it's not easy to make a track plan because of the fixed points (bridge, tunnel, turnout, catenary system, etc.) to be avoided due to the geographic conditions or to be passed for utilization of existing structures. In this study, when the horizontal and vertical curves are superimposed, in order to optimize the horizontal curve in aspect of the ride comfort, the object function $P_{CT}$ was developed and verified by vehicle dynamic analysis. Also, the solution algorithm for simplified evaluation method was presented.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.438-446
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• 1999

Crop minimization of the top and bottom ends of hot rolled plate, in a plate, in a plate mill, has been investigated. The existing model to determine the edging pattern at the finishing rolling pass was not reasonable to get high width accuracy and rolling yields. New models including width prediction have been formulated by using neural network model of back propagation learning algorithm and statistical analysis based on the actual production rolling data to give the optimal pattern for minimizing trimming loss. Using these models, at a given rolling condition of broadside pass and finishing pass and the permissible condition of width variation, it was possible to minimize crip at the top and bottom ends according to optimum procedure in plate mill. An application to improve the plan view pattern reduced width variation by 23% and crop length by 30% on average with an effective fishtail crop shape.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.1-7
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• 1993

This paper proposed an algorithm that extracts the optimum characteristics parameters to identify the signatures from the spectrum using 2-D FFT. The signature image input through a scanner is normalized into 250*128 pixels in the prepocessor. Normalized image is divided into block segments and each segment is transformed into space spectrum by 2-d FFT. There are several methods extracting the signature characteristic parameters from that spectrum. The result of experimentations which use the characteristic parameters extracted between $0^{\circ}and\;90^{\circ}$ in (0, 0), (63, 0) corners from 64$\times$64 block spectrum shows that the signature identification rate using that method gives 92.5% of successful achievement for 100 signatures, higher than the others.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.295-297
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• 2007

We design a new rate-3/2 full-diversity orthogonal space-time block code (STBC) for QPSK and 2 transmit antennas (TX) and 4 transmit antennas (TX) by enlarging the signalling set from the set of quaternions used in the Alamouti[I] and extendedcode and using additional members of the set of orthogonal matrices or Quasi-orthogonal matrices and higher than rate-5/4. Selective power scaling of information symbols is used to guarantee full-diversity while maximizing the coding gain (CG) and minimizing the transmitted signal peak-to-minimum power ratio (PMPR). The optimum power scaling factor is derived analytically and shown to outpetform schemes based only on constellation rotation while still enjoying a low-complexity maximum likelihood (ML) decoding algorithm.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.4
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• pp.317-326
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• 2008

The main purpose of the present study is to perform shape optimizations of transonic compressor blade in order to enhance its performance. In this study, the Latin hypercube sampling of design of experiments and the weighted average surrogate model with the help of a gradient based optimization algorithm are used within design space by the lower and upper limits of each design variable and for finding optimum designs, respectively. 3-D Reynolds-averaged Navier-Stokes solver is used to evaluate the objective functions of adiabatic efficiency and pressure ratio. Six variables from lean and airfoil thickness profile are selected as design variables. The results show that the adiabatic efficiency is enhanced by 1.43% by efficiency optimization while the pressure ratio is increased very small, and pressure ratio is increased by 0.24% by pressure ratio optimization.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1089-1103
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• 2000

A Problem of relevant interest to some industries is that of obtaining optimum two-dimensional layout. To solve this provlem, one is given a number of rectangular sheets and an order for a specified number of each of certain types of two-dimensional regular and irregular shapes. The aim is to cut the the shapes out of the sheets in such a way as to minimize the amount of waste produced. A DCS (Distributed Control System) is an integrated system which applies the decentralization concept to a control system handling both sequential and analog control. A DCS performs many operations such as data gathering, data processing, data storing and monitoring the operatin conditions for the operator. IN this paper, we propose a genetic algorithm based on rotation parameters from which the best pattern of layout is found as well as a layout method for better performance time. A DCS for the plate cutting process system, which is performed by a virtual system, is also identified.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1430-1435
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• 2003

Satellite upper platform is optimized by response surface method which has non-gradient, semi-glogal, discrete and fast convergency characteristics. Sampling points are extracted by design of experiments using Central Composite Method and Factorial Design. Also response surface is generated by the various regression functions. Structure analysis is execuated with regard for static and dynamic environment in launching stage. As a result response surface method is superior to other optimization method with respect to optimum value and cost of computation time. Also a confidence is varified in the various regression models.