• Title/Summary/Keyword: Real-time parameter estimation

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Fast Estimation of Low Frequency Parameter for Real-Time Analysis in Wide Area Systems (광역계통의 실시간해석을 위한 고속 저주파수 파라미터 추정)

  • Kim, Eun-Ju;Shim, Kwan-Shik;Kim, Yong-Gu;Kim, Eui-Sun;Nam, Hae-Kon;Lim, Young-Chul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.6
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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.

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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    • v.28 no.1
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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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Intelligent quality estimation system using primary circuit variables of RSW (저항점용접 1차 공정변수를 이용한 지능형 용접품질 판단 시스템)

  • 조용준;이세헌;신현일;배경민;권태용
    • Proceedings of the KWS Conference
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    • 1999.10a
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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.

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Real-Time Implementation of the Relative Position Estimation Algorithm Using the Aerial Image Sequence (항공영상에서 상대 위치 추정 알고리듬의 실시간 구현)

  • Park, Jae-Hong;Kim, Gwan-Seok;Kim, In-Cheol;Park, Rae-Hong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.3
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    • pp.66-77
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    • 2002
  • This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

Online Estimation of Rotational Inertia of an Excavator Based on Recursive Least Squares with Multiple Forgetting

  • Oh, Kwangseok;Yi, Kyong Su;Seo, Jaho;Kim, Yongrae;Lee, Geunho
    • Journal of Drive and Control
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    • v.14 no.3
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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.

An Approach to Walsh Functions for Parameter Estimation of Distributed Parameter Systems (WALSH함수의 접근에 의한 분포정수계의 파라메타 추정)

  • 안두수;배종일
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.7
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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.

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Determination of State-Space Model for Parameter Estimation of Tank Model (탱크모형의 매개변수추정을 위한 상태공간모형의 결정)

  • 이관수;이영석;정일광
    • Water for future
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    • v.28 no.2
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    • pp.125-136
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    • 1995
  • The propose of this study is improve the uncertainty of parameter choice of tank model by the trials and errors method. The real time prediction of parameter by using the Kalman filter is practiced to get the effective prediction algorithm of low flow runoff. Even though the total discharge of runoff through the orifice of each tank should be similar to the observed discharge, the tank model which can show the various basin characteristic is influenced by the runoff circumstances. As a result of the real-time estimation of the tank model parameter by the state-space type of Kalman filter, the variation of runoff circumstances is static when the convergence of observed value and estimated value keeps the ficed high point. The parameter of tank model which is estimated by Kalman filter shows good result for low flow and reasonable adaptability where flow change abruptly. The Kalman filter method is proved to give better result than Automatic structure estimation method.

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Online Parameter Estimation and Convergence Property of Dynamic Bayesian Networks

  • Cho, Hyun-Cheol;Fadali, M. Sami;Lee, Kwon-Soon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.4
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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.

Development of Simple Dynamic Models for Ship Manoeuvring Simulation (선박 조종 시뮬레이션을 위한 단순 기동 모델 개발)

  • Kim, Dong-Jin;Yeo, Dong-Jin;Rhee, Key-Pyo
    • Journal of the Korea Society for Simulation
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    • v.19 no.3
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    • pp.17-25
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    • 2010
  • It is necessary for the ship dynamic models to realize ship dynamics and to achieve the real-time analysis in the manoeuvring simulation. Generally, simple dynamic models, such as 1st-order differential equation models of turning angle, turning rate, and forward speed, are used in the manoeuvring simulation for multiple ships. Ship dynamic modeling and parameter estimation methods based on its turning test results are proposed in this paper. Parameter estimation methods for the constant speed model and the speed-changing model are mathematically developed and verified by comparing with turning test results of a real ship.

Comparison of Estimation Methods in NONMEM 7.2: Application to a Real Clinical Trial Dataset (실제 임상 데이터를 이용한 NONMEM 7.2에 도입된 추정법 비교 연구)

  • Yun, Hwi-Yeol;Chae, Jung-Woo;Kwon, Kwang-Il
    • Korean Journal of Clinical Pharmacy
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    • v.23 no.2
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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.