• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.457-460
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• 1996

An adaptive pH control is developed to manipulate the nonlinearities and time-varying properties of pH systems. In this research, we estimate two adjustable parameters by using the recursive least squares method and a nonlinear PI controller is used to control pH systems based on the estimated two parameters.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.376-386
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• 1995

Designs for polynomial approximation to the unknown response function are considered. Optimality criteria are monotone functions of the mean squared error matrix of the least squares estimator. They correspond to the classical A-, D-, G- and Q-optimalities. Optimal first order designs are chosen from the invariant designs and then compared with optimal second order designs.

• Journal of Electrical Engineering and Technology
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• 제11권5호
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• pp.1195-1201
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• 2016

• Smart Structures and Systems
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• 제12권6호
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.

• 전기학회논문지
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• 제59권10호
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• pp.1874-1881
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• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• Communications for Statistical Applications and Methods
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• 제18권6호
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• pp.761-770
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• 2011

회귀모형에 연관성이 높은 설명변수들이 포함되면 다중공선성의 문제가 야기되며, 동시에 자료에 회귀 이상점들이 포함되면 최소자승추정량에 바탕을 둔 제반 통계적 추론은 심각한 결함을 갖게 된다. 이러한 현상들은 데이터마이닝 분야에서 많이 볼 수 있는데, 본 논문에서는 두 가지 문제를 동시에 해결하기 위한 방안으로서 로버스트주성분회귀를 제안하였다. 특히 최적의 주성분을 선정하기 위한 새로운 기준을 개발하였는데, 설명변수들의 표본공분산 대신에 MVE-추정량을 기반으로 하였으며, 고유치가 아니라 상태지수의 크기에 바탕을 둔 선정기준을 제안하였다. 그리고 주성분모형에서의 추정을 위하여 회귀이상점에 대해 로버스트한 LTS-추정을 도입하였다. 제안된 선정기준이 기존의 기준들보다 다중공선성과 이상점이 유발하는 문제들을 잘 해결할 수 있음을 모의실험을 통하여 확인하였다.

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 2000년도 추계 학술발표회 논문집
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• pp.111-114
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• 2000

본 논문은 선형모델의 모델 계수의 결정방법으로 사용되는 최소자승법 (Least Squares Method, LSM)의 단점을 해결하기 위해 해석적으로 계산된 자료를 함께 적용하는 방법과 원자로의 출력분포 측정을 위한 SAM (Shape Annealing Matrix) 결정에 적용한 결과를 기술하고 있다. 해석적 자료를 함께 적용할 경우 연료 연소에 따른 원자로 특성변화를 적절히 반영하여 LSM 추정치의 정확도를 크게 개선할 수 있음을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.288-295
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• 1995

In this paper a hypotheses test procedure based on the least absolute deviation estimators for the unknown parameters in nonlinear regression models is investigated. The asymptotic distribution of the proposed likelihood ratio test statistic are established voth under the null hypotheses and a sequence of local alternative hypotheses. The asymptotic relative efficiency of the proposed test with classical test based on the least squares estimator is also discussed.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.507-518
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• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1640-1641
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• 2007

In this paper, an experiment of weighted robust least squares frequency estimation for the Gaussian envelope chirp signal which is used in the time-frequency domain reflectometry system was carried out. By incorporating the forgetting factor to the frequency estimator, the weighted robust least squares filter achieved good enough frequency estimation performance for the chirp signal and it can be adopted to implement not only low cost time-frequency domain reflectometry but also real-time time-frequency domain reflectometry implementation.