• Title/Summary/Keyword: Error estimator

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The Study on Autonomous State Estimator for Smart Grid (스마트그리드를 위한 자율형 상태관측기 연구)

  • Park, Jong-Chan;Lee, Se-In
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.60 no.1
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    • pp.32-36
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    • 2011
  • In this study, authors have proposed the autonomous state estimation which has been composed with IEC61850, GPS time synchronization and objective model design concept. The proposed method is able to supervise/correct measurement and communication error from SCADA. The major advantages of the proposed autonomous state estimation are that it is possible to evaluate integrity of data measured and transferred from SCADA, to reduce human intervention and to expense national-size applications such as EMS (Energy Management System), WAMS (Wide Area Monitoring System) or WAPS (Wide Area Protection System). This study addresses the issues related to the operation of the smart grid and proposes a new automated approach to achieve this goal. Through applying the proposed system to IEEE 14-bus test electric system, we prove the possibility of the proposed idea.

Inertia and Coefficient of Friction Estimation of Electric Motor using Recursive Least-Mean-Square Method (순환 최소자승법을 이용한 전동기 관성과 마찰계수 추정)

  • Kim, Ji-Hye;Choi, Jong-Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.2
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    • pp.311-316
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    • 2007
  • This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

Improved Instantaneous Reactive Power Compensator Applied Sensorless Control of IPMSM with Adaptive Back EMF and Current Model Observer (개선된 순시 무효전력 보상기와 함께 적용된 적응 역기전력과 전류 모델 관측기 적용한 돌극형 영구자석 동기 전동기의 센서리스 제어)

  • Lee, Joonmin;Park, Soon-je;Hong, Ju-Hoon;Kim, Woohee;Kim, Young Seok
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.934-935
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    • 2015
  • This paper presents the sensorless control method that employs the adaptive back-EMF(Electromotive Force) and current model observer of interior permanent magnet synchronous motor(IPMSM). The estimated back EMF considering a saliency is obtained by using the adaptive control method. The estimated EMF is inputted to the current model observer which is connected in series with adaptive back EMF estimator and is used to estimate the position and speed of the rotor. In order to improve the shortcomings of conventional method using the current error components multiplied in the compensation constant, the modified instantaneous reactive power compensator is applied. The validity of the control system presented is verified by the simulation.

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Comparison of Recognition Performance for Preprocessing Method of USE STSA with Approximated Modified Bessel Function (Modified Bessel 함수 근사화를 적용한 MMSE STSA 전처리 기법의 음성인식 성능 비교)

  • Son Jong Mok;Kim Min Sung;Bae Keun Sung
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.125-128
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    • 2001
  • 본 연구에서는 음성신호의 왜곡에 대해 음성 부재 확률을 고려한 MMSE(Minimum Mean Square Error) STSA(Short-Time Spectral Amplitude Estimator)를 전처리기로 도입하여 HMM(Hidden Markov Model)에 기반 한 음성인식시스템의 인식성능을 평가하였다. 음성인식 시스템의 실시간 구현을 고려하여, MMSE STSA 기법을 음성개선을 위한 전처리기로 사용할 때 MMSE STSA의 이득계산 과정에서 많은 계산량이 요구되는 modified Bessel 함수를 근사 화하여 사용하였다.

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Cluster-Based Quantization and Estimation for Distributed Systems

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.14 no.4
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    • pp.215-221
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    • 2016
  • We consider a design of a combined quantizer and estimator for distributed systems wherein each node quantizes its measurement without any communication among the nodes and transmits it to a fusion node for estimation. Noting that the quantization partitions minimizing the estimation error are not independently encoded at nodes, we focus on the parameter regions created by the partitions and propose a cluster-based quantization algorithm that iteratively finds a given number of clusters of parameter regions with each region being closer to the corresponding codeword than to the other codewords. We introduce a new metric to determine the distance between codewords and parameter regions. We also discuss that the fusion node can perform an efficient estimation by finding the intersection of the clusters sent from the nodes. We demonstrate through experiments that the proposed design achieves a significant performance gain with a low complexity as compared to the previous designs.

SIMULTANEOUS SPEED AND ROTOR TIME CONSTANT IDENTIFICATION OF AN INDUCTION MOTOR DRIVE BASED ON THE MODEL REFERENCE ADAPTIVE SYSTEM COMBINED WITH A FUZZY RESISTANCE ESTIMATOR

  • Soltani, Jafar;Mizaeian, Behzad
    • Proceedings of the KIPE Conference
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    • 1998.10a
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    • pp.11-16
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    • 1998
  • In this paper, simultaneous estimation of rotor speed and time constant for a voltage source inverter (VSI) fed induction motor drive are disccussed. The theory is based on the Model Reference Adaptive System (MRAS). The identifier executes Simultaneous rotor speed and time constant so that vector control of the induction may be achieved in the rotor-flux oriented reference frame. Furthermore, to eliminate the offset error caused by the change in the stator resistance, a fuzzy resistance regulator is also designed which operates in parallel with the rotor speed and time constant identifier

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State Estimation and Identification of Nonlinear Systems by Hermitian Expansion of Probability Distributions (Hermite전개법에 의한 비선형계의 상태추정 및 동정에 관한 연구)

  • Kyong Ki Kim
    • 전기의세계
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    • v.22 no.3
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    • pp.49-62
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    • 1973
  • An algorithm for the state estimation and identification of multivariable nonlinear systems with noisy nonlinear observation has been investigated on the basis of the multidimensional Hermitian expansion for the a posteriori probability densities of the predicted observation, the predicted state and the observation conditioned by the state. A new approach for construction of this sequential nonlinear estimator, retaining up to the second order term of the observation error, has been developed, along with the approximation of nonlinear system functions, truncating at the second term. The estimation of the unknown parameters has been established by extending the state estimation technique, regarding the parameters as another state variables. The results of investigation indicate the feasibility of the schemes presented in this paper.

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Families of Estimators of Finite Population Variance using a Random Non-Response in Survey Sampling

  • Singh, Housila P.;Tailor, Rajesh;Kim, Jong-Min;Singh, Sarjinder
    • The Korean Journal of Applied Statistics
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    • v.25 no.4
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    • pp.681-695
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    • 2012
  • In this paper, a family of estimators for the finite population variance investigated by Srivastava and Jhajj (1980) is studied under two different situations of random non-response considered by Tracy and Osahan (1994). Asymptotic expressions for the biases and mean squared errors of members of the proposed family are obtained; in addition, an asymptotic optimum estimator(AOE) is also identified. Estimators suggested by Singh and Joarder (1998) are shown to be members of the proposed family. A correction to the Singh and Joarder (1998) results is also presented.

An Estimator of Population Mean Based on Balanced Systematic Sampling When Both the Sample Size and the Reciprocal of the Sampling Fraction are Odd Numbers

  • Kim, Hyuk-Joo
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.667-677
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    • 2007
  • In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

Estimation on the Generalized Half Logistic Distribution under Type-II Hybrid Censoring

  • Seo, Jung-In;Kim, Yongku;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.20 no.1
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    • pp.63-75
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    • 2013
  • In this paper, we derive maximum likelihood estimators (MLEs) and approximate maximum likelihood estimators (AMLEs) of unknown parameters in a generalized half logistic distribution under Type-II hybrid censoring. We also obtain approximate confidence intervals using asymptotic variance and covariance matrices based on the MLEs and the AMLEs. As an illustration, we examine the validity of the proposed estimation using real data. Finally, we compare the proposed estimators in the sense of the mean squared error (MSE), bias, and length of the approximate confidence interval through a Monte Carlo simulation for various censoring schemes.