• Title/Summary/Keyword: Parameter estimator

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Rotor flux Observer Using Robust Support Vector Regression for Field Oriented Induction Mmotor Drives (유도전동기 벡터제어를 위한 Support Vector Regression을 이용한 회전자자속 추정기)

  • Han Dong Chang;Back Woon Jae;Kim Sung Rag;Kim Han Kil;Lee Suk Gyu;Park Jung IL
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.2
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    • pp.70-78
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    • 2005
  • In this paper, a novel rotor flux estimation method of an induction motor using support vector regression(SVR) is presented. Two well-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. Training of SVR which the theory of the SVR algorithm leads to a quadratic programming(QP) problem. The proposed SVR rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of proposed algorithm are throughly verified through numerical simulation.

On the Number of Modes Required to Observe Forces in Flexible Structures (유연 구조물에서 반력 평가를 위해 요구되는 모드의 수)

  • Kim, Joo-Hyung;Kim, Sang-Sup
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.1
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    • pp.150-157
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    • 2002
  • The number of required modes to provide accurate force information in a truncated model of a flexible structure is investigated. In the case of modal truncation of a distributed parameter system, the difference in convergence rates between displacements and forces is discussed. The residual flexibility. a term from past literature, is used to recapture some of the lost force information in a truncated model. This paper presents numerical and experimental results of a study where the residual flexibility is used in conjunction with a Kalman filter so that accurate force information may be obtained from a small set of displacement measurements wish a reduced-order model. The motivation for this paper is to be able to obtain accurate information about unmeasurable dynamic reaction forces in a rotating machine for diagnostic and control purposes.

Residual-based copula parameter estimation (잔차를 이용한 코플라 모수 추정)

  • Na, Okyoung;Kwon, Sunghoon
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.267-277
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    • 2016
  • This paper considers we consider the estimation of copula parameters based on residuals in stochastic regression models. We prove that a semiparametric estimator using residual empirical distributions is consistent under some conditions and apply the results to the copula-ARMA model. We provide simulation results for illustration.

Objective Bayesian inference based on upper record values from Rayleigh distribution

  • Seo, Jung In;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.411-430
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    • 2018
  • The Bayesian approach is a suitable alternative in constructing appropriate models for observed record values because the number of these values is small. This paper provides an objective Bayesian analysis method for upper record values arising from the Rayleigh distribution. For the objective Bayesian analysis, the Fisher information matrix for unknown parameters is derived in terms of the second derivative of the log-likelihood function by using Leibniz's rule; subsequently, objective priors are provided, resulting in proper posterior distributions. We examine if these priors are the PMPs. In a simulation study, inference results under the provided priors are compared through Monte Carlo simulations. Through real data analysis, we reveal a limitation of the appropriate confidence interval based on the maximum likelihood estimator for the scale parameter and evaluate the models under the provided priors.

Non-convex penalized estimation for the AR process

  • Na, Okyoung;Kwon, Sunghoon
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.453-470
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    • 2018
  • We study how to distinguish the parameters of the sparse autoregressive (AR) process from zero using a non-convex penalized estimation. A class of non-convex penalties are considered that include the smoothly clipped absolute deviation and minimax concave penalties as special examples. We prove that the penalized estimators achieve some standard theoretical properties such as weak and strong oracle properties which have been proved in sparse linear regression framework. The results hold when the maximal order of the AR process increases to infinity and the minimal size of true non-zero parameters decreases toward zero as the sample size increases. Further, we construct a practical method to select tuning parameters using generalized information criterion, of which the minimizer asymptotically recovers the best theoretical non-penalized estimator of the sparse AR process. Simulation studies are given to confirm the theoretical results.

A Study on Individual Tap-Power Estimation for Improvement of Adaptive Equalizer Performance

  • Kim, Nam-Yong
    • Journal of electromagnetic engineering and science
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    • v.4 no.1
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    • pp.23-29
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    • 2004
  • In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

Position-Speed Estimator using Kalman Filter with Parameter Identification (기계적인 시정수의 동정을 가지는 Kalman 필터를 사용한 위치-속도 추정자)

  • Shin, Ki-Sang;Lee, Je-Hie;Huh, Uk-Youl
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.434-436
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    • 1997
  • 본 연구에서는 저속에서 발생하는 측정잡음에 대한 문제를 불규칙 확률시스템으로 고려하여 Kalman 필터를 관측자로서 사용하고 고속에서뿐만 아니라 저속에서의 위치와 속도 추정성능을 향상시키고자 한다. Kalman 필터는 확률적 외란을 포함하고 있는 동적시스템에 적용되는 최적상태 추정자이다. 또한 이 Kalman 필터는 외란을 가지는 이산형 실시간 동적 처리 시스템에서 최적의 미지 상태를 추정하기 위해 선형, 불편향, 그리고 최소 오차분산 회귀형 알고리즘을 제공한다. 또한, MRAS(Model Reference Adaptive System) 방법을 이용하여 모터와 부하에 대응되는 기계적 시정수를 동정한다. 이 방법은 기계적인 시정수가 알려지지 않은 시스템에 적용하여 위치와 속도의 추정을 가능하게 하기 위해서이다. 더욱이 동정의 결과를 이용하여 Kalman 필터 알고리즘에 적용한다.

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Optimum multi-objective modified step-stress accelerated life test plan for the Burr type-XII distribution

  • Srivastava, P.W.;Mittal, N.
    • International Journal of Reliability and Applications
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    • v.15 no.1
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    • pp.23-50
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    • 2014
  • This paper deals with formulation of optimum multi-objective modified step-stress accelerated life test (ALT) plan for Burr type-XII distribution under type-I censoring. Since it is impractical to estimate only one objective parameter after conducting costly ALT tests; also, it is not desirable to assume instantaneous changes in stress levels because of limited capacity of test equipments and the presence of undesirable failure modes, therefore, an optimum multi-objective modified step-stress ALT plan has been designed. The optimal test plan consists in determining the optimum low stress level and optimal time at which stress starts linearly increasing from low stress by minimizing the weighted sum of the asymptotic variances of the maximum likelihood estimator of quantile lifetimes at design constant stress. The method developed has been illustrated using an example. Sensitivity analysis has been carried out. Comparative study has also been done to highlight the merits of the proposed model.

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Length-biased Rayleigh distribution: reliability analysis, estimation of the parameter, and applications

  • Kayid, M.;Alshingiti, Arwa M.;Aldossary, H.
    • International Journal of Reliability and Applications
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    • v.14 no.1
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    • pp.27-39
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    • 2013
  • In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

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The Algorithm of Sweep-the-Negatives and its Applications to Order Resticted Inference

  • Kim, Byong-Dok;Park, Jae-Rong;Akio Kudo
    • Journal of the Korean Statistical Society
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    • v.19 no.1
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    • pp.54-70
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    • 1990
  • Consider the extreme problem : min$(\mu-y)'(\mu-y)$ subject to $A\mu \geq 0$, where A is an $n \times p$ matrix, which often occurs in solving the maximum likelihood estimator with ordered restrictions in parameter space. In case the matrix AA' has all non-positive off-diagonal elements, some propositions in this paper guarantee that the above extreme solutions are achieved at most at n sweep out steps in Gaussian eliminations. Some typicla examples of Sweep-the-Negatives method are given.

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