• 제목/요약/키워드: least square technique

검색결과 378건 처리시간 0.028초

Phasor Estimation Algorithm Based on the Least Square Technique during CT Saturation

  • Lee, Dong-Gyu;Kang, Sang-Hee;Nam, Soon-Ryul
    • Journal of Electrical Engineering and Technology
    • /
    • 제6권4호
    • /
    • pp.459-465
    • /
    • 2011
  • A phasor estimation algorithm based on the least square curve fitting technique for the distorted secondary current due to current transformer (CT) saturation is proposed. The mathematical form of the secondary current during CT saturation is represented as the scaled primary current with magnetizing current. The information on the scaled primary current is estimated using the least square technique, with the measured secondary current in the saturated section. The proposed method can estimate the phasor of a fundamental frequency component during the saturated period. The performance of the algorithm is validated under various fault and CT conditions using a C400 CT model. A series of performance evaluations shows that the proposed phasor estimation algorithm can estimate the phasor of the fundamental frequency component with high accuracy, regardless of fault conditions and CT characteristics.

Reexamination of Estimating Beta Coecient as a Risk Measure in CAPM

  • Phuoc, Le Tan;Kim, Kee S.;Su, Yingcai
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제5권1호
    • /
    • pp.11-16
    • /
    • 2018
  • This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

최소자승법을 이용한 원판형 절리의 직경분포와 체적빈도 추정에 관한 연구 (A Study on the Estimation of Diameter Distribution and Volumetric Frequency of Joint Discs Using the Least Square Method)

  • 송재준
    • 터널과지하공간
    • /
    • 제15권2호
    • /
    • pp.137-144
    • /
    • 2005
  • 이 연구에서는 최소자승법을 이용하여 절리의 직경분포를 추정하는 방법을 개발하였다. 이전에 Song and Lee가 제안한 방법에서는 현장에서 조사한 양끝내포선(contained trace) 분포로부터 무한 조사창에서 정의되는 절리선(joint trace) 길이 분포를 먼저 구하고 이 후에 직경분포를 구하게 된다. 그러나 새로 제안한 방법을 사용하면 중간 추정과정없이 현장에서 얻은 양끝내포선 분포로부터 바로 절리의 직경분포를 구할 수 있다. 이전의 방법과 비교할 때 새로 제안된 방법은 표본의 크기가 작을 때 조금 더 높은 추정정밀도를 보이며, 직경분포를 추정하는 과정에서 절리의 기하학적 파라미터의 하나인 체적빈도(volumetric frequency)도 제공한다. 새로운 추정법의 검증을 위해 Monte Carlo 시뮬레이션을 적용하였다.

최소자승법을 이용한 $Y-\triangle$ 누설 인덕턴스 추정 방법 (Leakage Inductance Estimation of $Y-\triangle$ Transformer Using the Least Square Method)

  • 황태근;이병은;장성일;김용균;강용철
    • 전기학회논문지
    • /
    • 제56권4호
    • /
    • pp.645-650
    • /
    • 2007
  • This paper proposes a parameter estimation technique of a power transformer. Based on the combined equation, it estimates separately the primary and secondary leakage inductances using the least square method from the instantaneous voltages and currents in the steady state. The performance of the proposed technique was investigated by varying the cut-off frequency of the filter and the number of samples per cycle. The estimated values are obtained based on the average value for 41 cycle.

전최소자승법을 이용한 강인한 모드매개변수 (Robust Modal Parameter Idnentification Using Total Least Square Method)

  • 정의봉;김준엽;김현
    • 대한기계학회논문집A
    • /
    • 제20권3호
    • /
    • pp.843-849
    • /
    • 1996
  • The least square estimation is used frequently in experimental modal analysis techinque to eliminate noise signals. However, identified modal parameters are sometimes inaccurate, since the least squre estimation is sensitive to noise. In this paper, a new total least squre estimation, which is robust to noise signals, is developed and applied to experimental modal analysis technique such as Prony method and Circle Fit method. Several simulated results show that the proposed method is robuster to noise than conventional method.

MFXLMS 알고리즘을 이용한 전자기배어링계의 외란 보상 제어기 - 이론 (Disturbance Compensation Control of An Active Magnetic Bearing System by Multiple FXLMS Algorithm - Theory)

  • 강민식;정종수
    • 한국정밀공학회지
    • /
    • 제21권2호
    • /
    • pp.74-82
    • /
    • 2004
  • In this paper, a disturbance feedforward compensator design technique is proposed for an active magnetic bearing system subject to base motion for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feedforward compensator design based on adaptive estimation by means of the Multiple Filtered-x least mean square(MFXLMS) algorithm is proposed. The performance and the effectiveness of the proposed technique will be presented in the succeeding paper in which the proposed technique is applied to a 2-DOF active magnetic bearing system subject to base motion.

An Adaptive Tracking Controller for Vibration Reduction of Flexible Manipulator

  • Sung Yoon-Gyeoung;Lee Kyu-Tae
    • International Journal of Precision Engineering and Manufacturing
    • /
    • 제7권3호
    • /
    • pp.51-55
    • /
    • 2006
  • An adaptive tracking controller is presented for the vibration reduction of flexible manipulator employed in hazardous area by combining input shaping technique with sliding-mode control. The combined approach appears to be robust in the presence of severe disturbance and unknown parameter which will be estimated by least-square method in real time. In a maneuver strategy, it is found that a hybrid trajectory with a combination of low frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid body trajectory alone which many researchers have employed. The feasibility of the adaptive tracking control approach is demonstrated by applying it to the simplified model of robot system. For the applications of the proposed technique to realistic systems, several requirements are discussed such as control stability and large system order resulted from finite element modeling.

최소자승법을 이용한 Y-$\Delta$ 변압기 파라미터 추정 방법 (Parameter Estimation of Y-$\Delta$ Transformer Using the Least Square Method)

  • 강용철;황태근;이병은;장성일;김용균
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2007년도 제38회 하계학술대회
    • /
    • pp.42-43
    • /
    • 2007
  • This paper proposes a parameter estimation technique of a power transformer. Based on the combined equation, it estimates separately the primary and secondary leakage inductances, winding resistances using the least square method from the instantaneous voltages and currents in the steady state. The performance of the proposed technique was investigated by varying the cut-off frequency of the filter and the number of samples per cycle. The technique estimates the parameters with higher sampling frequencies.

  • PDF

Data-driven approach to machine condition prognosis using least square regression trees

  • Tran, Van Tung;Yang, Bo-Suk;Oh, Myung-Suck
    • 한국소음진동공학회:학술대회논문집
    • /
    • 한국소음진동공학회 2007년도 추계학술대회논문집
    • /
    • pp.886-890
    • /
    • 2007
  • Machine fault prognosis techniques have been considered profoundly in the recent time due to their profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are forecasted precisely before they reach the failure thresholds. In this work, we propose an approach of Least Square Regression Tree (LSRT), which is an extension of the Classification and Regression Tree (CART), in association with one-step-ahead prediction of time-series forecasting technique to predict the future conditions of machines. In this technique, the number of available observations is firstly determined by using Cao's method and LSRT is employed as prognosis system in the next step. The proposed approach is evaluated by real data of low methane compressor. Furthermore, the comparison between the predicted results of CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers a potential for machine condition prognosis.

  • PDF