• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제12권3호
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• pp.153-160
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• 2008

A size-biased Poisson distribution is defined. Its characterization by using a recurrence relation for first order negative moment of the distribution is obtained. Different estimation methods for the parameter of the model are also discussed. R-Software has been used for making a comparison among the three different estimation methods.

• 대한수학회보
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• 제33권3호
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• pp.377-383
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• 1996

We consider in this paper the following nonlinear regression model $$ (1.1) y_t = f(x_t, \theta_o) + \in_t, t = 1, \ldots, n, $$ where $y_t$ is the tth response, $x_t$ is m-vector imput variable, $\theta_o$ is a p-vector of unknown parameter belong to a parameter space $\Theta, f:R^m \times \Theta \ to R^1$ is a nonlinear known function, and $\in_t$ are independent unobservable random errors with finite second moment.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 추계학술대회 논문집
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• pp.18-20
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• 2004

In this paper, a new technique of inertia identification using recursive least square algorithm and full order estimator is proposed. The speed response is sensitive to variation in machine parameters especially the moment of inertia. The effectiveness of the method has been verified by simulations.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.387-394
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• 2004

Zero-Inflated Poisson distribution is Poisson distribution with excess zeros. Recently defects of product hardley happen in the manufacturing process. In this case it is desirable to apply to the Zero-Inflated Poisson distribution rather than Poisson. Our target of this paper is to study the tests for changes of rate of defects after the unknown change-point. We are going to compare the powers of the two proposed tests with likelihood tests by the simulations.

• International Journal of Reliability and Applications
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• 제2권1호
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.

• 대한의용생체공학회:의공학회지
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• 제37권1호
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• pp.21-30
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• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.

• 전력전자학회논문지
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• 제18권3호
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• pp.232-239
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• 2013

This paper proposes an improved stator flux estimator through ensuring conventional PLPF to act as a pure integrator for sensorless control of induction motors. Conventional PLPF uses the estimated synchronous speed as a cut-off frequency and has the gain and phase compensators. The gain and phase compensators are determined on the assumption that the estimated synchronous angular speed is coincident with the real speed. Therefore, if the synchronous angular speed is not same as the real speed, the gain and phase compensation will not be appropriate. To overcome the problem of conventional PLPF, this paper analyzes the relationship between the synchronous speed error and the phase lag error of the stator flux. Based on the analysis, this paper proposes the synchronous speed error compensation scheme. To achieve a start-up without speed sensor, the current model is used as the stator flux estimator at the standstill. When the motor starts up, the current model should be switched into the voltage model. So a stable transition between the voltage model and the current model is required. This paper proposes the simple transition method which determines the initial values of the voltage model and the current model at the transition moment. The validity of the proposed schemes is proved through the simulation results and the experimental results.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.211-218
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• 2014

Qu et. al. (2000) proposed the quadratic inference functions (QIF) method to marginal model analysis of longitudinal data to improve the generalized estimating equations (GEE). It yields a substantial improvement in efficiency for the estimators of regression parameters when the working correlation is misspecified. But for the longitudinal data with time-dependent covariates, when the implicit full covariates conditional mean (FCCM) assumption is violated, the QIF can not provide more consistent and efficient estimator than GEE (Cho and Dashnyam, 2013). Lai and Small (2007) divided time-dependent covariates into three types and proposed generalized method of moment (GMM) for longitudinal data with time-dependent covariates. They showed that their GMM type II and GMM moment selection methods can be more ecient than GEE with independence working correlation (GEE-ind) in the case of type II time-dependent covariates. We develop upgraded QIF method for type II time-dependent covariates. We show that this upgraded QIF method can provide substantial gains in efficiency over QIF and GEE-ind in the case of type II time-dependent covariates.

• 자동차안전학회지
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• 제5권1호
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• pp.62-68
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• 2013

This paper describes development of 4 Wheel Drive (4WD) Electric Vehicle (EV) based driving control algorithm for severe driving situation such as icy road or disturbance. The proposed control algorithm consists three parts : a supervisory controller, an upper-level controller and optimal torque vectoring controller. The supervisory controller determines desired dynamics with cornering stiffness estimator using recursive least square. The upper-level controller determines longitudinal force and yaw moment using sliding mode control. The yaw moment, particularly, is calculated by integration of a side-slip angle and yaw rate for the performance and robustness benefits. The optimal torque vectoring controller determines the optimal torques each wheel using control allocation method. The numerical simulation studies have been conducted to evaluated the proposed driving control algorithm. It has been shown from simulation studies that vehicle maneuverability and lateral stability performance can be significantly improved by the proposed driving controller in severe driving situations.

• 한국지능시스템학회논문지
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• 제16권5호
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• pp.601-607
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• 2006

본 논문은 칼만필터를 이용한 ZMP의 다음 상태 예측을 통한 새로운 이족로봇의 균형제어기법을 제안한다. 일반적으로 이족로봇의 동역학 모델은 3D-LIPM(3D-Linear Inverted Pendulum Mode)에 의해 수학적으로 근사화되지만, 이는 로봇의 동역학적 특성을 완벽하게 표현할 수 없다. 이족로봇의 안정성은 ZMP(Zero Moment Point) 위치가 안정영역에 존재하는 경우에 안정성이 보장된다. 그리고 로봇 구조와 그 모델 사이의 내재된 오차는 로봇의 안정성에 영향을 끼칠 수 있다. 그러므로 본 논문에서 제안하는 균형제어기법은 내부 오차를 줄일 수 있으며, 적절한 로봇의 제어가 가능하다. 제안된 균형제어기법의 실험은 다양한 상황을 포함한 가상의 공간상에서 모의실험 되었다.