• 제목/요약/키워드: Robust estimator

검색결과 278건 처리시간 0.028초

디지털 IP 제어기를 이용한 브러시리스 직류 전동기의 센서리스 속도제어 (Sensorless Speed Control for Brushless DC Motor using Digital IP Controller)

  • 김종선;박형준;장재훈;유지윤;서삼준
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2004년도 전력전자학술대회 논문집(1)
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    • pp.289-293
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    • 2004
  • The sensorless speed control technique for BLDCM using digital IP control is proposed in this paper for advanced speed characteristic which is robust for loads. The sensorless drive of BLDCM using terminal voltages is affected by load or speed because it uses analog filters to estimate the rotor position. For this reason, the robust speed controller with the accurate rotor position estimator is needed for sensorless control which is robust to load and insensitive to motor parameters. The constant speeds robust to load variation and the stable sensorless control of BLDCM robust to the increase or decrease of speed with constant load are implemented using digital IP control in this paper. The validity to these is established with experimentation.

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스트랩다운 적외선 영상센서를 위한 관성센서 기반 강인최소자승 움직임 훼손영상 복원 기법 (Robust Least Squares Motion Deblurring Using Inertial Sensor for Strapdown Image IR Sensors)

  • 김기승;나성웅
    • 제어로봇시스템학회논문지
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    • 제18권4호
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    • pp.314-320
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    • 2012
  • This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

지대공 유도탄 기체진동 제거를 위한 강인 벤딩 주파수 추정필터 (A Robust Bending Frequency Estimator for SAM Application)

  • 나원상;송찬호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2152-2154
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    • 2004
  • A robust bending frequency tracker is proposed to design the adaptive notch filter which removes the time-varying missile structural mode from the sensor measurements. To design the bending frequency tracker, firstly, the signal model is derived from the input-output relationship of Nehorai notch filter structure. Also, the time-varying nature of the bending frequency is modelled as the norm-bounded uncertainty. Based on the uncertain signal model, it is shown that the design problem of robust bending frequency tracker can be casted into that of adaptive robust $H_{\infty}$ filter or equivalently robust LMS filter.

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The Identification Of Multiple Outliers

  • Park, Jin-Pyo
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.201-215
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    • 2000
  • The classical method for regression analysis is the least squares method. However, if the data contain significant outliers, the least squares estimator can be broken down by outliers. To remedy this problem, the robust methods are important complement to the least squares method. Robust methods down weighs or completely ignore the outliers. This is not always best because the outliers can contain some very important information about the population. If they can be detected, the outliers can be further inspected and appropriate action can be taken based on the results. In this paper, I propose a sequential outlier test to identify outliers. It is based on the nonrobust estimate and the robust estimate of scatter of a robust regression residuals and is applied in forward procedure, removing the most extreme data at each step, until the test fails to detect outliers. Unlike other forward procedures, the present one is unaffected by swamping or masking effects because the statistics is based on the robust regression residuals. I show the asymptotic distribution of the test statistics and apply the test to several real data and simulated data for the test to be shown to perform fairly well.

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Subset Selection Procedures Based on Some Robust Estimators

  • Song, Moon-Sub;Chung, Han-Yeong;Bae, Wha-Soo
    • Journal of the Korean Statistical Society
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    • 제11권2호
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    • pp.109-117
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    • 1982
  • In this paper, a preliminary study is performed on the subset selection procedures which are based on the trimmed means and the Hodges-Lehmann estimator derived from the Wilcoxon test. The proposed procedures are compared to the Gupta's rule through a small smaple Monte Carlo study. The results show that the procedures based on the robust estimators are successful in terms of efficiency and robustness.

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On Confidence Intervals of High Breakdown Regression Estimators

  • Lee Dong-Hee;Park YouSung;Kim Kang-yong
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.205-210
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    • 2004
  • A weighted self-tuning robust regression estimator (WSTE) has the high breakdown point for estimating regression parameters such as other well known high breakdown estimators. In this paper, we propose to obtain standard quantities like confidence intervals, and it is found to be superior to the other high breakdown regression estimators when a sample is contaminated

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망각소자를 갖는 t-분포 강인 연속 추정을 이용한 음성 신호 추정에 관한 연구 (Robust Sequential Estimation based on t-distribution with forgetting factor for time-varying speech)

  • 이주헌
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1998년도 제15회 음성통신 및 신호처리 워크샵(KSCSP 98 15권1호)
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    • pp.470-474
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    • 1998
  • In this paper, to estimate the time-varying parameters of speech signal, we use the robust sequential estimator based on t-distribution and, for time-varying signal, introduce the forgetting factor. By using the RSE based on t-distribution with small degree of freedom, we can alleviate efficiently the effects of outliers to obtain the better performance of parameter estimation. Moreover, by the forgetting factor, the proposed algorithm can estimate the accurate parameters under the rapid variation of speech signal.

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신경망 외란관측기와 파라미터 보상기를 이용한 PMSM의 정밀 위치제어 (Precision Position Control of PMSM using Neural Network Disturbance Observer and Parameter Compensator)

  • 고종선;이태훈
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2003년도 춘계전력전자학술대회 논문집(1)
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    • pp.393-397
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    • 2003
  • This paper presents neural load torque observer tha used to deadbeat load torque observer and regulation of the compensation gun by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator li combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper

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역기전력 추정기를 이용한 전류 모델 기반의 SPMSM 센서리스 벡터제어 (Current Model based SPMSM Sensorless Vector Control using Back Electro Motive Force Estimator)

  • 이정효;유재성;공태웅;이원철;원충연
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2007년도 추계학술대회 논문집
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    • pp.7-10
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    • 2007
  • The current model based sensorless method has many benefits that it can be robust control for large load torque. However, this method should determine a coefficient of back electro motive force(back-emf). This coefficient is varied by load torque and speed. Also, the coefficient determining equation is not exist, so it is determined only by experiment. On the other hands, using only back-emf estimatior method can not drive in low speed area and it has weakness in load variation. For these problems, this paper suggests the hybrid sensorless method that mixes the back-emf estimator regarding saliency and the current based sensorless model. This estimator offers not only non-necessary coefficient for current sensorless model, but also wide speed area operating in no specific transition method.

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Robust Discriminant Analysis using Minimum Disparity Estimators

  • 조미정;홍종선;정동빈
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.135-140
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    • 2004
  • Lindsay and Basu (1994)에 의해 소개된 최소차이추정량 (Minimum Disparity Estimators)들은 실제 자료 분석 도구로써 유용하다. 본 논문에서는 최소일반화음지수 차이추정량 (Minimum Generalized Negative Exponential Disparity Estimator, MGNEDE)이 최대가능도추정량 (Maximum Likelihood Estimator, MLE)와 최소가중 헬링거거리추정량 (Minimum Blended Weight Hellinger Distance Estimator, MBWHDE)에 비해 오염된 정규모형에서 효율적이고 로버스트하다는 것을 모의실험을 통하여 확인하였다. 또한 세 가지 추정량들에 의해 추정된 모수들을 이용하여 판별하였을 때 자 추정량득의 판별율을 비교함으로써 오염된 정규모형에서 MLE의 대안으로 MGNEDE와 MBWHDE를 사용할 수 있음을 보였다.

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