• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.10
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• pp.2667-2677
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• 1995

A new numerical algorithm using equal order linear finite element and fractional step method has been developed which is capable of analyzing unsteady fluid flow and heat transfer problems. Streamline Upwind Petrov-Galerkin (SUPG) method is used for the weighted residual formulation of the Navier-Stokes equations. It is shown that fractional step method, in which pressure term is splitted from the momentum equation, reduces computer memory and computing time. In addition, since pressure equation is derived without any approximation procedure unlike in the previously developed SIMPLE algorithm based FEM codes, the present numerical algorithm gives more accurate results than them. The present algorithm has been applied preferentially to the well known bench mark problems associated with steady flow and heat transfer, and proves to be more efficient and accurate.

• Journal of KSNVE
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• v.10 no.5
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• pp.838-842
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• 2000

The vibration of an axially moving string is studied when the string has geometric non-linearity and translating acceleration. Based upon the von karman strain theory, the equations of motion are derived considering the longitudinal and transverse deflection. The equation for the longitudinal vibration is linear and uncoupled, while the equation for the transverse vibration is non-linear and coupled between the longitudinal and transverse deflections. These equations are discretized by using the Galerkin approximation after they are transformed into the variational equations, i.e. the weak forms so that the admissible and comparison functions can be used for the bases of the longitudinal and transverse deflections respectively. With the discretized nonlinear equations, the time responses are investigated by using the generalized-$\alpha$ method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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• pp.805-810
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• 1989

This paper presents a method for planning reactive power compensation such as shunt capacitors and reacters so as to maintain bus voltage in acceptable range during steady state operation in power system. The algorithm in this paper decomposes the problem into reactive power planning module for the compensation of bus voltage and load flow module for adjusting the error resulted from the linear approximation. A planning technique is based on linear programming to minimize the amount of added reactive power compensation in each case. Transformer tap settings and generator voltages are adjusted to minimize the compensation. The constraints are the operation limits of the control variables and bus voltages. The result of one sample system is presented to confirm the practical use of the proposed algorithm.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.1-16
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• 2007

In this paper, we derive exact explicit expressions for the triple and quadruple moments of the lower record values from inverse the Weibull (IW) distribution. Next, we present and calculate the coefficients of the best linear unbiased estimates of the location and scale parameters of IW distribution (BLUEs) for different choices of the shape parameter and records size. We then use the higher order moments and the calculated BLUEs to compute the mean, variance, and the coefficients of skewness and kurtosis of certain linear functions of lower record values. By using the coefficients of the skewness and kurtosis, we develop approximate confidence intervals for the location and scale parameters of the IW distribution using Edgeworth approximate values and then compare them with the corresponding intervals constructed through Monte Carlo simulations. Finally, we apply the findings of the paper to some simulated data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.85-93
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• 1998

In general, the solvability of linear robust output regulation problem are not preserved under time-sampling. Thus, it is found that the digital regulator implemented by time-sampling of analog output regulator designed based on the continuous-time linear system model is nothing but a 1st order approximation with respect to time-sampling. However, one can design an improved sampled-data regulator with respect to sampling time by utilizing teh intrinsic structure of the system. In this paper, we study the system structures for which it is possible to design an improved sampled-data regulator with respect to sampling time.

• Journal of Ocean Engineering and Technology
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• v.13 no.1 s.31
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• pp.51-61
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• 1999

When a structure is built on the ground under consolidation, the instant corresponding contact pressure which the upper structure exerts on the ground is established. But, as the consolidation of the ground proceeds, the contact pressure is changed because of the flexural rigidity of the upper structure. This varied contact pressure exerts influence on the consolidation behavior of the ground. And, this varied consolidation behavior exerts on the contact pressure in retum. This kind of interaction between the upper struture and the olwer ground under consolidation contimues till all the consolidation process in finished. So this problem cannot be defined as a linear problem. In this paper an approximation method which can analyse this non-linear interaction problem is proposed by the FEM.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1037-1047
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• 2012

The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.171-180
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• 1993

Variables, x and y are said to have a linear relation if $y={\beta}_0+{\beta}_1\;x$, and ${\beta}_0$ and ${\beta}_1$ are constants. The relationship is called a structural relationship if x has positive variance (i.e., x is not fixed) and only error-prone measurements of x and y can be obtained. This paper derives (to order $n^{+1/2}$) an approximate distribution of the Studentized test statistic for testing hypotheses about the slope parameter, ${\beta}_1$ in a simple linear structural model. A simulation study suggests our approximate distribution is more accurate approximation to the exact distributions of the Studentized statistic than is the limiting distribution.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.69-78
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• 2019

A structured model with both single-index and varying coefficients is a powerful tool in modeling high dimensional data. It has been widely used because the single-index can overcome the curse of dimensionality and varying coefficients can allow nonlinear interaction effects in the model. For high dimensional index vectors, variable selection becomes an important question in the model building process. In this paper, we propose an efficient estimation and a variable selection method based on a smoothing spline approach in a partially linear single-index-coefficient regression model. We also propose an efficient algorithm for simultaneously estimating the coefficient functions in a data-adaptive lower-dimensional approximation space and selecting significant variables in the index with the adaptive LASSO penalty. The empirical performance of the proposed method is illustrated with simulated and real data examples.