• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.996-1003
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• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.323-337
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• 2004

This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.94-100
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• 2003

In this paper, we study the estimation of reliability function for a parallel system with k dependent exponential components. We assume that the failure of one of the k components changes the life distribution of the remaining components. Also, we compare with Cramer-Rna lower bound for variances of the minimum variance unbiased estimator, and the mean square errors of the maximum likelihood estimator of reliability system with the through the Monte Carlo simulation.

• Journal of Korean Society for Quality Management
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• v.9 no.1
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• pp.3-11
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• 1981

A stress-strength model is formulated for s of k systems consisting of identical components. We consider minimum variance unbiased (MVU) estimation of system reliability for data consisting of a random sample from the stress distribution and one from the strength distribution when the two distirubtions are Weibull with unknown scale parameters and same known shape parameter. The asymptotic distribution of MVU estimate of system reliability in the model is obtained by using the standard asymptotic properties of the maximum likelihood estimate of system reliability and establishing their equivalence. Uniformly most accurate unbiased confidence intervals are also obtained for system reliability. Empirical comparison of the two estimates for small samples is studies by Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.1
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• pp.67-76
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• 1990

For a two-parameter Pareto distribution, the uniformly minimum variance unbiased estimateors(UMVUE) for the function of the two parameters are expressed in terms of confluent hypergeometric function. The variance of the UMVUE is also expressed in terms of hypergeometric function of several variables. UMVUE's for the ${\gamma}th$ moment about zero and several useful parametric functions, and their variances are obtained as special cases. The estimators of Baxter(1980) and Saksena and Johnson(1984) are special cases of our estimator.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.580-588
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• 2009

In this study daily flow rates and delivered pollutant loads of Nakdong river basin are simulated with modified TANK model and minimum variance unbiased estimator. Based on the simulation results, flow duration curves, load duration curves, and delivery ratio duration curves have been established. Then GIS analysis is performed to obtain several hydrological geomorphic characteristics such as watershed area, stream length, watershed slope and runoff curve number. Finally, multiple regression analysis is carried out to estimate empirical equations for pollutants delivery ratio. The results show that there is positive relation between the flow rates and delivery ratios, and the proposed empirical formulas for delivery ratio can predict well river pollutant loads.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.847-856
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• 2013

In this paper, we deal with testing goodness-of-fit for normal distribution based on parametric and nonparametric entropy estimators. The minimum variance unbiased estimator for the entropy of the normal distribution is derived as a parametric entropy estimator to be used for the construction of a test statistic. For a nonparametric entropy estimator of a data-generating distribution under the alternative hypothesis sample entropy and its modifications are used. The critical values of the proposed tests are estimated by Monte Carlo simulations and presented in a tabular form. The performance of the proposed tests under some selected alternatives are investigated by means of simulations. The results report that the proposed tests have better power than the previous entropy-based test by Vasicek (1976). In applications, the new tests are expected to be used as a competitive tool for testing normality.

• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.538-550
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• 2012

This study suggests a general methodology which is designed for assessing RDOC behavior at the catchment scale by coupling properly a series of steam flow and water quality simulation models and actual monitoring data set. The modified TANK model in which a river routing function is incorporated to the conventional one is applied to simulate the long-term daily stream flow data, and the simulated stream flow data is combined with the 7-parameter log-linear model coupled to the minimum variance unbiased estimator to simulate the long-term daily water quality (BOD, COD and TOC) loads. Finally, the regression analysis between the usually monitored water quality data (BOD, COD and TOC) and RDOC is combined with the simulated water quality data to manifest the spatio-temporal variability of RDOC flux behavior at the Korean TMDL catchment scale.