• 전자공학회논문지B
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• 제32B권1호
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• pp.85-95
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• 1995

The error intensity models for the ML estimation of a signal parameter have been developed in a companion paper [1]. While the methods described in [1] are applicable to any estimation problem with continuous parameters, our main application in this paper is the time delay estimation, and comparisons among the models derived in [1] (i.e. LC, LM, and ALM models)have been made. We first consider the case where only additive Gaussian noise is involved, and then the shot noise environment where coherent impulsive noise is also involved in addition to the Gaussian noise. We compare the models in terms of the probability of error, MSE(Mean Squared Error), and the computational complexity, which are the most important performance criteria in the analysis of parameter estimation. In conclusion, the ALM model turned out to be the most adequate model of all from the viewpoints of the criteria mentioned above.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.644-649
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• 2006

In this paper, a methodology for estimating the model parameters of a discrete-time system and tuning a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems regarding parameter estimation and controller tuning, pseudo-parallel genetic algorithms(PPGAs) are used. The parameters of a discrete-time system are estimated using both the model adjustment technique and a PPGA. The digital PID controller is described by the pulse transfer function and then its three gains are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

• 한국방재학회 논문집
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• 제10권6호
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• pp.131-138
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• 2010

본 연구에서는 저류함수법의 매개변수 추정을 위해 개발한 범용모형을 토대로 관측수문자료를 보유하고 있는 16개 댐유역에 적용하여 그 적정성을 확인하였다. 저류함수법의 기존 매개변수 추정식은 대부분 한정된 조건에서 얻어졌고 다양한 유역특성을 고려할 때 물리적 의미가 없는 값이 얻어지는 경우가 많아 미계측유역에서 적용이 회피되어 왔다. 본 연구에서 개발된 매개변수 추정결과는 이러한 문제를 보이지 않으면서도 다양한 유역특성인자의 변화에 민감하게 반응할 수 있는 특성을 보여주고 있었다. CN방법에 의해 직접적으로 도출된 유효우량과 함께 범용모형을 이용한 매개변수 추정을 토대로 미계측유역에서 저류함수법의 활용성을 높일 수 있을 것으로 기대된다.

• 한국지반공학회논문집
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• 제20권2호
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• pp.125-130
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• 2004

본 논문에서는 수치적 구성방정식인 연속 탄소성 캡 모델의 정수추정에 관한 방법이 제시되었다. 캡 모델을 이용하여 실제 토질의 거동을 예측하기 위하여서는 캡 모델을 이루는 토질의 물성과 직접적으로 연관된 여덟개의 정수가 결정되어야 한다. 이를 위하여 첫 번째로, Ottawa 모래를 사용하여 표준압밀시험기를 이용한 일축압축시험 및 배수삼축압측 시험이 토질거동의 실제기준값으로서 수행되었고, 두 번째로 탄소성 캡 수치해석모델의 반응을 실내실험값에 일치시키기 위하여 추정된 정수들을 사용한 수치실험이 수행되었다. 두 실험 간의 오차를 최소화하기 위하여 최적화 기법이 사용되었으며, 최적화 후 결정된 8개의 정수는 실내실험결과와 비교되었다. 특히, 수치적 삼축압축시험시 응력계산에 따른 수평변위 측정에 특별한 주의가 필요하다.

• Journal of Power Electronics
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• 제17권2호
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• pp.398-410
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• 2017

This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate ($LiFePO_4$) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.

• Communications for Statistical Applications and Methods
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• 제25권4호
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• 전자공학회논문지B
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• 제30B권5호
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• International Journal of Reliability and Applications
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• 제18권2호
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• pp.83-98
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• 2017

Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.271-276
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• 1997

A dynamic discount approach is proposed for the estimation of the Poisson parameter and the forecasting of the Poisson random variable, where the parameter of the Poisson distribution varies over time intervals. The recursive estimation procedure of the Poisson parameter is provided. Also the forecasted distribution of the Poisson random variable in the next time interval based on the information gathered until the current time interval is provided.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.755-762
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• 2013

본 논문은 NHPP 소프트웨어 신뢰성모형에서 모수추정과 고장시간에 대한 예측을 다루고자 한다. 소프트웨어 신뢰성모형 Goel-Okumoto모형에서 평균값 함수에 대한 최우추정과 경험적 사전분포를 가정한 공액사전분포에서 베이지안 추정을 다루었다. 실제 자료에서 두 가지 추정법에 의한 모수 추정값을 제공하였으며, 모형의 적합성을 판정하고, 고장수에 대한 예측값을 비교하였다.