• Communications of the Korean Mathematical Society
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• v.13 no.4
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• pp.865-874
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• 1998

A modulus of continuity on the increments of a two-parameter Gaussian process is obtained via estimating large deviation probability inequalities on the suprema of the Gaussian process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.995-1000
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• 2010

With the development of the auto industry, the automobile manufacturers demand to shorten development period and reduce the cost. Compared with the traditional method, applying the virtual prototype is more economical. This paper presents a method for parameters sensitivity analysis and optimizing the performance of vehicle noise and vibration. The existing design processes were repeatedly analyzed with a focus on vehicle performance to decide the design parameters of dimension, thickness, mounting type of body and chassis systems in the vehicle development period. This paper describes the prediction technique of vehicle performance using L18 orthogonal array layout, quality deviation analysis and parameter sensitivity analysis for robust design. This paper analyzed the performance correlation equation through the frequency and sensitivity database according to a design factor change. The new concept is that the performance prediction is possible without repeated activities of test and analysis. This paper described the parameter analysis applications such as bush dynamic stiffness and bush void direction of rear suspension. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce man hour and test development period as well as to achieve stable NVH performance.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.1
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• pp.71-78
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• 2011

In this paper, the effect of parameter errors to the estimation of the rotor angle in sensorless operation of a permanent magnet synchronous motor is analyzed. The angle error information which is utilized to estimate the rotor position can be classified into two factors, namely, the sign factor and the gain factor. This paper particularly focuses on parameter errors reflected in the sign factor of the angle error information which causes a deviation in the angle estimation. In this paper, mathematical expressions describing the deviation of the angle estimation due to the inductance error and the resistance error in the sensorless control are derived. The validity of the expression is verified by the computer simulations and the experimental results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.180-185
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• 1988

This paper considers the problem of the optimal input design for parameter estimtion in the ARMAX model in which the system and noise transfer function have the common denominator polynomial. Deriving the information matrix, in detail, for the assumed model structure and using the autocorrelation functin of the filtered input as design variables, it is shown that D-optimal input signal can be realized as an autoregressive moving average process. Computer simulations are carried out to show the standard-deviation reduction in the parameter estimtes using the optimal input signal.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.99-109
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• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.460-467
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• 2010

In this study, the parameters of the feedwater control system (FWCS) of the OPR1000 type nuclear power plant (NPP) are optimized by response surface methodology (RSM) in order to acquire better level control performance from the FWCS. The objective of the optimization is to minimize the steam generator (SG) water level deviation from the reference level during transients. The objective functions for this optimization are relationships between the SG level deviation and the parameters of the FWCS. However, in this case of FWCS parameter optimization, the objective functions are not available in the form of analytic equations and the responses (the SG level at plant transients) to inputs (FWCS parameters) can be evaluated by computer simulations only. Classical optimization methods cannot be used because the objective function value cannot be calculated directely. Therefore, the simulation optimization methodology is used and the RSM is adopted as the simulation optimization algorithm. Objective functions are evaluated with several typical transients in NPPs using a system simulation computer code that has been utilized for the system performance analysis of actual NPPs. The results show that the optimized parameters have better SG level control performance. The degree of the SG level deviation from the reference level during transients is minimized and consequently the control performance of the FWCS is remarkably improved.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.89-94
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• 2006

In this paper, the effects of the system parameters on the high cycle fatigue life based on structural dynamic analysis of a turbine blade are investigated. Conventional studies have forcused on the fatigue life of turbine blades with specific system parameters. However, each parameter has statistical deviation because of inhomogeneity of material property, tolerance, and operating conditions. Therefore a methodology that estimates the effects of system parameter on the fatigue lift deviation is demonstrated.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.1-10
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• 2002

Information on the distribution of the basic random variables is essential for the accurate evaluation of structural reliability. The usual method for determining the distribution is to fit a candidate distribution to the histogram of available statistical data of the variable and perform appropriate goodness-of-fit tests. Generally, such candidate distributions would have two parameters that may be evaluated from the mean value and standard deviation of the statistical data. In the present paper, a-parameter Gamma distribution, whose parameters can be directly defined in terms of the mean value, standard deviation and skewness of available data, is suggested. The flexibility and advantages of the distribution in fitting statistical data and its significance in structural reliability evaluation are identified and discussed. Numerical examples are presented to demonstrate these advantages.