• 전기학회논문지
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• 제58권6호
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• pp.1078-1086
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• 2009

This paper presents a Fourier based algorithm for estimating the parameters of the low frequency oscillating modes. The proposed methods estimates various parameters(frequency, damping factor, mode magnitude, phase) by fitting Fourier spectrum and phase with a damped exponential cosine function. Dominant frequency is selected by taking frequency corresponding to the peak spectrum, and damping factor is estimated using the left/right spectra of Fourier spectrum. In addition, mode magnitude is calculated by the normalized peak spectrum, and phase is estimated from spectrum phase. Also, we introduce an accuracy index in order to determine the accuracy of the estimated parameters, and the index is calculated using the deviations of the peak spectrum and the left/right spectra. The parameter estimation methods proposed in this paper include very simple arithmetical processes, so the algorithms are simple and the calculation speed is very fast. The proposed methods are applied to test functions with two dominant modes. The results show that the proposed methods are highly applicable to low frequency parameter estimation.

• 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.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1999년도 특별강연 및 추계학술발표대회 개요집
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• pp.142-145
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• 1999

The dynamic resistance monitoring is one of the important issues in that in-process and real time quality assurance of resistance spot weld is needed to increase the product reliability. Secondary dynamic resistance patterns, as a real manner, are hard to adapt those factors in real time and in-plant system. In the present study, a new dynamic resistance detecting method is presented as a practical manner of weld quality assurance at the primary circuit. By the correlation analysis, it is found that the primary dynamic resistance patterns are basically similar to those of the secondary. Various dynamic resistance indices are characterized with the primary curve. And quality of the weld, like the tensile shear strength, is estimated using adaptive neuro-fuzzy estimation system which is consisted of the Sugeno fuzzy algorithm. Through the fuzzy clustering and parameter optimization, real time weld quality assurance system with less efforts is proposed.

• 대한전자공학회논문지SP
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• 제39권3호
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• pp.66-77
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• 2002

본 논문에서는 TMS320C80 멀티미디어 MVP(multimedia video processor)를 이용한 항법 변수 추출의 구현 기법에 관하여 연구하였다. 특히, 항법 변수 추출 시스템의 실시간 구현에 중요한 역할을 하는 상대 위치 추정 알고리듬의 실시간 구현 방법에 관하여 고찰한다. 두 지점에서 취득된 영상을 이용하는 상대위치 추정 알고리듬을 근간으로 하여, 방대한 양의 계산량을 감축하면서 고정 소수점 프로세서에 적합한 고속 알고리듬을 개발한다. 그런 다음, MVP 내의 4개의 병렬 프로세서(PP; parallel processor)를 이용하여 병렬 처리할 수 있도록 알고리듬을 재구성한다. 그 결과, MVP를 이용한 항법 변수 추출 시스템은 초당 30프레임을 처리할 수 있음을 확인하여, 실시간 구현 조건을 만족시킴을 알 수 있었다.

• 드라이브 ㆍ 컨트롤
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• 제14권3호
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• pp.40-49
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• 2017

This study presents an online estimation of an excavator's rotational inertia by using recursive least square with forgetting. It is difficult to measure rotational inertia in real systems. Against this background, online estimation of rotational inertia is essential for improving safety and automation of construction equipment such as excavators because changes in inertial parameter impact dynamic characteristics. Regarding an excavator, rotational inertia for swing motion may change significantly according to working posture and digging conditions. Hence, rotational inertia estimation by predicting swing motion is critical for enhancing working safety and automation. Swing velocity and damping coefficient were used for rotational inertia estimation in this study. Updating rules are proposed for enhancing convergence performance by using the damping coefficient and forgetting factors. The proposed estimation algorithm uses three forgetting factors to estimate time-varying rotational inertia, damping coefficient, and torque with different variation rates. Rotational inertia in a typical working scenario was considered for reasonable performance evaluation. Three simulations were conducted by considering several digging conditions. Presented estimation results reveal the proposed estimation scheme is effective for estimating varying rotational inertia of the excavator.

• 대한전기학회논문지
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• 제39권7호
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• pp.740-748
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• 1990

In this paper, we consider the problem of parameter estimation, i.e., definding the internal structure of a linear distribution parameter system from its input/output data. First, a linear partial differential equation describing the system is double-integrated with respect to two variables and then transformed into an integral equation. Next the Walsh Operation Matrix for Walsh function and their integration are introduced to transform the integral equation into algebraic simultaneous equations. Finally, we develop an algorithm to estimate the parameters of the linear distributed parameter system from the simple linear algebraic simultaneous equations. It is also shown that our algorithm could be effective in real time data processing since it uses the Fast Walsh Transform.

• 물과 미래
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• 제28권2호
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• pp.125-136
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• 1995

본 연구의 목적은 탱크모형의 매개변수를 시행착오범으로 산정할 경우, 불확실성을 개선하기 위해 Kalman filter로 매개변수를 실시간 예측하여 저수유출의 예측에 효과적인 알고리즘을 얻고자 하였다. 유역특성을 다양한 구조로 나타낼 수 있는 탱크모형은 각 단 탱크에 부착된 유출공으로부터 유출한 총 유출량이 관측유량에 유사하게 나타나야 하지만 유출환경의 영향으로 수렴성이 좋지 않았다. 이러한을 보완하기 위하여 탱크모형의 매개변수를 Kalman filter의 상태공간 모형에 의하여 실시간으로 추정한 결과, 시간 경과에 따라 추정치와 관측치의 수렴도가 높아 일정한 값을 유지하였으며, 이때의 유출환경을 나타내는 상태공간의 매개변수변화가 정적임을 알 수 있었다. 따라서 Kalman filter에 의한 탱크모형의 매개변수 추정기법은 저수유출 예측에 특히 효율성이 좋았으며 유량이 급변하는 곳에서도 어느 정도 적응하여 기존 탱크모형의 구조를 자동기법으로 정하는 예측시스템 보다 유출예측 시스템에 의한 탱크모형의 구조적 알고리즘이 적합한 모형임을 입증하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.285-294
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• 2007

In this paper, we investigate a novel online estimation algorithm for dynamic Bayesian network(DBN) parameters, given as conditional probabilities. We sequentially update the parameter adjustment rule based on observation data. We apply our algorithm to two well known representations of DBNs: to a first-order Markov Chain(MC) model and to a Hidden Markov Model(HMM). A sliding window allows efficient adaptive computation in real time. We also examine the stochastic convergence and stability of the learning algorithm.

• 한국시뮬레이션학회논문지
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• 제19권3호
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• pp.17-25
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• 2010

선박 조종 시뮬레이션을 구성하는 기동 모델은 대상 선박의 동역학적인 특성을 현실에 가깝게 구현해야 하며, 신속한 계산 및 결과 처리가 가능하여야 한다. 다중 선박을 대상으로 하는 실시간 조종 시뮬레이션에서는 계산 시간 단축을 위해 일반적으로 선회각이나 선회율, 또는 전진 속도에 대한 1차 미분방정식 모델을 사용하여 선박의 움직임을 구현하게 된다. 본 논문에서는 대상 선박의 선회 시험 정보가 주어져 있을 경우 이를 이용한 선박의 단순 기동 모델링 및 계수 추정법을 제안하였다. 전진속도가 일정한 모델과 전진 속도의 변화를 고려한 모델의 계수 추정법을 수학적으로 전개하였으며, 실선 선회 시험 자료를 이용하여 제안된 모델의 유용성을 검증하였다.

• 한국임상약학회지
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• 제23권2호
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.