• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.420-422
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• 1998

In this paper, we propose a position-speed control of servo system with a state estimator. And also we utilized two mass modelling in order to deals with real system accurately. The overall control system consists of two parts: the position-speed controller and state 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 minimun error variance recursive algorithm to estimate the unknown state optimally. Therefore we consider the error problem about the servo system modelling, the measurement noise at low-speed ranges a stochastic system, and implement a optimal state observer. Performance of the proposed state estimator are demonstrated by computer simulations.

• 응용통계연구
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• 제14권1호
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• pp.13-24
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• 2001

이중추출에서 모평균 추정방법을 고찰하였다. 전통적으로 널리 쓰이는 비추정량과 회귀추정량 그리고 비례배분 및 Rao 배분을 한 후의 층화평균에 대하여 주어진 기대 비용에서 최적의 표본수, 최소분산 및 분산추정량을 살펴보았다. 또한 비추정 및 층화의 효과를 모두 내포하는 결합비 추정량을 제안하고 주어진 기대 비용에서 최적의 표본수 및 최소분산을 유도하였고 분산추정량을 구하였다. 그리고 제한된 모의실험을 통하여 비추정량, 층화평균 및 결합비 추정량의 효율을 비교하였다. 모의실험 결과 비추정량과 층화평균은 경우에 따라 효율이 다르게 나타난 반면, 결합비 추정량은 대체로 두 방법보다 효율이 우수하게 나타나 결합비 추정량이 이중추출에 유용하게 쓰일 수 있음을 보였다.

• Communications for Statistical Applications and Methods
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• 제28권4호
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• pp.351-368
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• 2021

For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen's estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ². The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen's estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen's estimator when σ² is small and exhibits a meaningful decrease in the RMSE under moderate and large σ² values.

• Journal of the Korean Statistical Society
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• 제33권3호
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• pp.339-351
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• 2004

In this paper we generalize and improve the refined Pickands estimator of Drees (1995) for the extreme value index. The finite-sample performance of the refined Pickands estimator is not good particularly when the sample size n is small. For each fixed k = 1,2,..., a new estimator is defined by a convex combination of k different generalized Pickands estimators and its asymptotic normality is established. Optimal weights defining the estimator are also determined to minimize the asymptotic variance of the estimator. Finally, letting k depend upon n, we see that the resulting estimator has a better finite-sample behavior as well as a better asymptotic efficiency than the refined Pickands estimator.

• 제어로봇시스템학회논문지
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• 제8권1호
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• pp.60-66
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• 2002

In this paper, a new target pointing guidance algorithm is proposed by combining the optimal target pointing solution and a simple time-to-Go estimator. Also investigated are some properties of the guidance algorithm which include a relation to conventional PNG, convergence region and convergence trajectories of error states according to the time-to-go estimator gain. Some guidelines for designing the pointing guidance law are commented based on the convergence properties. A design example in the case of large initial heading errors is presented and its performance is investigated by simulation.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.619-626
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• 2003

Given a prior guess for the unknown value of P(Y

• Journal of the Korean Data and Information Science Society
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• 제22권3호
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• pp.575-587
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• 2011

We investigate some statistical properties of several dierence-based error variance estimators in nonparametric regression model. Most of existing dierence-based methods are developed under asymptotical properties. Our focus is on the exact form of mean and variance for the lag-k dierence-based estimator and the second-order dierence-based estimator in a nite sample size. Our approach can be extended to Tong's estimator (2005) and be helpful to obtain optimal k.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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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.

• 한국통신학회논문지
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• 제14권2호
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• pp.155-163
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• 1989

단일 링크 유연성 로보트 팔의 제어를 위해서 가정 모드 방법으로 유도된 동 특성 모델링에 QUADRATIC-최적제어 이론을 적용하였다. 이 제어 기법에 대한 제어 루우프 구성에는 모든 상태값의 피이트 백을 필요로 하지만 유연성 팔에 있어서 모드형태의 시 종속 변화율은 직접 출력으로부터 피이드백 될수 없기 때문에 최적 제어기를 실현하기 위해서는 상태 추정기의 도입이 필요하게 된다. 특히 시스템에 외란이나 측정에 노이즈가 발생할 때는 확률 추정 방법을 적용해서 상태를 추정해야 하는데 이를 위해서 칼만 필터를 사용하였다. 상태 추정기를 이용한 유연성 메니퓨레이터 팔의 시스템 모델을 모든 상태 값이 직접 측정될 수 있다고 가정한 유연성 시스템 모델과 시뮤레이션을 통해서 비교하였다.

• Journal of the Korean Statistical Society
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• 제33권4호
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• pp.435-447
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• 2004

In additive nonparametric regression, Linton and Nielsen (1995) showed that the marginal integration when applied to the local linear smoother produces a rate-optimal estimator of each univariate component function for the case where the dimension of the predictor is two. In this paper we give new formulas for the bias and variance of the marginal integration regression estimators which are valid for boundary areas as well as fixed interior points, and show the local linear marginal integration estimator is in fact rate-optimal when the dimension of the predictor is less than or equal to four. We extend the results to the case of the local polynomial smoother, too.