• 제목/요약/키워드: parameter estimator

검색결과 473건 처리시간 0.026초

와이블과정을 응용한 신뢰성 성장 모형에서의 MTBF 추정$^+$ (MTBF Estimator in Reliability Growth Model with Application to Weibull Process)

  • 이현우;김재주;박성현
    • 품질경영학회지
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    • 제26권3호
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    • pp.71-81
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    • 1998
  • In reliability analysis, the time difference between the expected next failure time and the current failure time or the Mean Time Between Failure(MTBF) is of significant interest. Until recently, in reliability growth studies, the reciprocal of the intensity function at current failure time has been used as being equal to MTBE($t_n$)at the n-th failure time $t_n$. That is MTBF($t_n$)=l/$\lambda (t_n)$. However, such a relationship is only true for Homogeneous Poisson Process(HPP). Tsokos(1995) obtained the upper bound and lower bound for the MTBF($t_n$) and proposed an estimator for the MTBF($t_n$) as the mean of the two bounds. In this paper, we provide the estimator for the MTBF($t_n$) which does not depend on the value of the shape parameter. The result of the Monte Carlo simulation shows that the proposed estimator has better efficiency than Tsokos's estimator.

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Hierarchical and Empirical Bayes Estimators of Gamma Parameter under Entropy Loss

  • Chung, Youn-Shik
    • Communications for Statistical Applications and Methods
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    • 제6권1호
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    • pp.221-235
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    • 1999
  • Let be $X_1$,...,$X_p$, $p\geq2$ independent random variables where each $X_i$ has a gamma distribution with $\textit{k}_i$ and $\theta_i$ The problem is to simultaneously estimate $\textit{p}$ gamma parameters $\theta_i$ and $\theta_i{^-1}$ under entropy loss where the parameters are believed priori. Hierarch ical Bayes(HB) and empirical Bayes(EB) estimators are investigated. And a preference of HB estimator over EB estimator is shown using Gibbs sampler(Gelfand and Smith 1990). Finally computer simulation is studied to compute the risk percentage improvements of the HB estimator and the estimator of Dey Ghosh and Srinivasan(1987) compared to UMVUE estimator of $\theta^{-1}$.

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A Robust Estimation for the Composite Lognormal-Pareto Model

  • Pak, Ro Jin
    • Communications for Statistical Applications and Methods
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    • 제20권4호
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    • pp.311-319
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    • 2013
  • Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

영구자석 동기전동기의 상수변동을 보상한 센서리스 제어 (Sensorless Control of a Permanent Magnet synchronous Motor with Compensation of the Parameter Variation)

  • 양순배;조관열;홍찬희
    • 전력전자학회논문지
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    • 제7권6호
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    • pp.517-523
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    • 2002
  • 영구자석 동기전동기의 전동기상수 변동을 보상한 센서리스 제어를 제안한다. 실제시스템의 d축 및 q축 전류와 위치 예측기의 전동기 모델의 d축 및 q축 전류의 차이를 이용하여 회전자의 위치를 예측한다. 전동기가 회전방향을 바꿀 때 발생하는 낮은 속도에서 고정자 저항을 검출하고 온도변화에 의한 고정자 저항 및 유기전압 상수의 변동을 보상한다. 또한 회전자 위치 예측기의 이득은 전동기 속도에 따라 보상된다.

Bayes and Sequential Estimation in Hilbert Space Valued Stochastic Differential Equations

  • Bishwal, J.P.N.
    • Journal of the Korean Statistical Society
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    • 제28권1호
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    • pp.93-106
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    • 1999
  • In this paper we consider estimation of a real valued parameter in the drift coefficient of a Hilbert space valued Ito stochastic differential equation. First we consider observation of the corresponding diffusion in a fixed time interval [0, T] and prove the Bernstein - von Mises theorem concerning the convergence of posterior distribution of the parameter given the observation, suitably normalised and centered at the MLE, to the normal distribution as Tlongrightarrow$\infty$. As a consequence, the Bayes estimator of the drift parameter becomes asymptotically efficient and asymptotically equivalent to the MLE as Tlongrightarrow$\infty$. Next, we consider observation in a random time interval where the random time is determined by a predetermined level of precision. We show that the sequential MLE is better than the ordinary MLE in the sense that the former is unbiased, uniformly normally distributed and efficient but is latter is not so.

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Estimation of the exponential distribution based on multiply Type I hybrid censored sample

  • Lee, Kyeongjun;Sun, Hokeun;Cho, Youngseuk
    • Journal of the Korean Data and Information Science Society
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    • 제25권3호
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    • pp.633-641
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    • 2014
  • The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

외란관측기와 파라미터 보상기를 이용한 PMSM의 정밀속도제어 (Precision Speed Control of PMSM Using Disturbance Observer and Parameter Compensator)

  • 고종선;이택호;김칠환;이상설
    • 전력전자학회논문지
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    • 제6권1호
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    • pp.98-106
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    • 2001
  • 본 논문에서는 영구자석 동기 전동기의 정밀 속도 제어의 방법으로 외란 관측기를 이용한 외란 보상방법과 파라미터 추정에 의해 보상기의 이득을 조절하도록 함으로서, 외란이 없는 등가 지표시스템의 응답 특성을 추정하도록 제안하였다. 외란 관측기에 의한 보상방법은 잘 알려진 데드비트 외란 관측기를 이용하였으며 잡음에 약한 데드비트 관측기의 단점을 보완하기 위하여 후단필터로서 MA처리를 통하여 잡음에 대한 영향을 줄이도록 하였다. 또한 관측기의 단점을 보완하기 위하여 후단필터로서 MA처리를 통하여 잡음에 대한 영향을 줄이도록 하였다. 또한 관측기의 파라미터와 실제 시스템의 파라미터의 차이로 발생하는 외란 추정 오차를 줄이고자 실제 시스템과 파라미터 보상기로 구성된 등가 시스템이 지표 시스템이 되도록 구성하였다. 시스템에 사용된 RLS파라미터 추정기는 외란에 의하여 편향된 추정 특성을 가진다. 이러한 파라미터 추정문제에 대하여 파라미터 추정기가 높은 성능을 갖는 데드비트 외란 관측기를 포함하도록 함으로서 외란에 의한 문제를 해결하였다. 이와 같이 제안된 제어기는 외란 및 파라미터 변화를 갖는 시스템에서 강인한 고정밀 제어를 할 수 있으며, 이의 안정성과 효용성을 컴퓨터를 이용한 모의 실험과 TMS320C31이 내장된 DS1102 DSP 보드를 이용하여 실험으로써 보였다.

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Improving $L_1$ Information Bound in the Presence of a Nuisance Parameter for Median-unbiased Estimators

  • Sung, Nae-Kyung
    • Journal of the Korean Statistical Society
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    • 제22권1호
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    • pp.1-12
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    • 1993
  • An approach to make the information bound sharper in median-unbiased estimation, based on an analogue of the Cramer-Rao inequality developed by Sung et al. (1990), is introduced for continuous densities with a nuisance parameter by considering information quantities contained both in the parametric function of interest and in the nuisance parameter in a linear fashion. This approach is comparable to that of improving the information bound in mean-unbiased estimation for the case of two unknown parameters. Computation of an optimal weight corresponding to the nuisance parameter is also considered.

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Adaptive Receding Horizon $H_{\infty}$ Controller Design for LPV Systems

  • P., PooGyeon;J., SeungCheol
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.535-535
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    • 2000
  • This paper presents an adaptive receding horizon H$_{\infty}$ controller for the linear parameter varying systems in the deterministic environment, which combines a parameter range estimator and a robust receding horizon H$_{\infty}$ controller using the parameter bounds. Using parameter set inclusion and terminal inequality condition, the closed-loop system stability is guaranteed. It is shown that the stabilizing adaptive receding horizon H$_{\infty}$ controller guarantees the H$_{\infty}$ norm bound.

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퍼지신경망과 강인한 마찰 상태 관측기를 이용한 비선형 마찰 서보시스템에 대한 강인 제어 (Robust Control for Nonlinear Friction Servo System Using Fuzzy Neural Network and Robust Friction State Observer)

  • 한성익
    • 한국정밀공학회지
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    • 제25권12호
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    • pp.89-99
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    • 2008
  • In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.