• 제목/요약/키워드: recursive least square method

검색결과 167건 처리시간 0.026초

수직축 선형 영구자석 동기전동기의 질량 추정 (Mass Estimation of a Permanent Magnet Linear Synchronous Motor Applied at the Vertical Axis)

  • 이진우;지준근;목형수
    • 전력전자학회논문지
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    • 제13권6호
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    • pp.487-491
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    • 2008
  • 선형 서보 응용분야에 사용되는 속도제어기를 정밀하게 조정하기 위해서는 부하를 포함한 가동부 전체의 정밀한 질량이 필요하다. 본 논문에서는 수직축 선형 영구자석 동기전동기의 가동부 질량을 추정하기 위한 방법으로 축차 최소자승 추정 알고리즘을 적용한 질량 추정방법을 제안한다. 먼저 수직축 선형 영구자석 동기 전동기의 기계적인 동적 시스템에 대한 DARMA(deterministic autoregressive moving average)모델을 유도하고, 유도된 DARMA모델에 축차 최소자승 추정 방법을 적용한 질량 추정방법을 제안하며, Matlab/Simulink를 이용한 시뮬레이션 및 실험 결과를 제시하여 제안한 방법으로 수직축 질량을 무부하 및 부하 시 모두 정밀하게 추정할 수 있음을 보였다.

직교 좌표에서 카메라 시스템의 방향과 위치 결정 (Determination of Camera System Orientation and Translation in Cartesian Coordinate)

  • 이용중
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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    • pp.109-114
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    • 2000
  • A new method for the determination of camera system rotation and translation from in 3-D space using recursive least square method is presented in this paper. With this method, the calculation of the equation is found by a linear algorithm. Where the equation are either given or be obtained by solving five or more point correspondences. Good results can be obtained in the presence if more than the eight point. A main advantage of this new method is that it decouple rotation and translation, and then reduces computation. With respect to error in the solution point number in the input image data, adding one more feature correspondence to required minimum number improves the solution accuracy drastically. However, further increase in the number of feature correspondence improve the solution accuracy only slowly. The algorithm proposed by this paper is used to make camera system rotation and translation easy to recognize even when camera system attached at end effecter of six degrees of freedom industrial robot manipulator are applied industrial field.

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하향식 기계학습의 반복적 오차 역투영에 기반한 고해상도 얼굴 영상의 복원 (Reconstruction of High-Resolution Facial Image Based on Recursive Error Back-Projection of Top-Down Machine Learning)

  • 박정선;이성환
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권3호
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    • pp.266-274
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    • 2007
  • 본 논문에서는 하향식 기계 학습 및 반복적 오차 역투영음 이용하여 한 장의 저해상도 얼굴 영상으로부터 고해상도 얼굴 영상을 복원하는 방법을 제안한다. 먼저 얼굴 영상을 독립된 형태 기저와 질감 기저의 선형 중첩으로 표현하고, 주어진 저해상도 얼굴 영상을 형태 기저와 질감 기저의 선형 중첩으 로 최대한 근사하게 표현할 수 있는 계수를 추정한다. 이 추정된 계수를 고해상도 얼굴 영상의 형태 기저 와 질감 기저의 선형 중첩 계수로 사용함으로써 고해상도 얼굴 영상을 복원한다. 또한, 복원된 고해상도 얼굴 영상의 정확도를 개선하기 위하여 학습 기반 오차 역투영 과정을 반복적으로 적용한다. 다양한 실험을 통하여, 제안된 방법이 저해상도 얼굴 영상으로부터 고해상도 얼굴 영상을 효과적으로 복원함을 입증하였으며, 이 방법을 사용하여 원거리 감시 시스템에서 획득된 저해상도 얼굴 영상을 고해상도 얼굴 영상으로 합성함으로써, 얼굴 인식 시스템의 성능을 높일 수 있음을 확인하였다.

다변수 자기동조 PID 제어기의 설계 (Design of multivariable self tuning PID controllers)

  • 조원철;전기준
    • 전자공학회논문지S
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    • 제34S권7호
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    • pp.66-77
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    • 1997
  • This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.

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Bispectrum을 이용한 EP 신호 복원에서의 Wiener process 응용 (Estimation of the Evoked Potential using Bispectrum with Confidence Thresholding)

  • 박정일;안창범
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 추계학술대회
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    • pp.265-268
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    • 1995
  • Signal averaging technique to improve signal-to-noise ratio has widely been used in various fields, especially in electrophysiology. Estimation of the EP(evoked potential) signal using the conventional averaging method fails to correctly reconstruct the original signal under EEG(electroencephalogram) noise especial]y when the latency times of the evoked potential are not identical. Therefore, a technique based on the bispectrum averaging was proposed for recovering signal waveform from a set o noisy signals with variable signal dalay. In this paper an improved bispectrum estimation technique of the RP signal is proposed using a confidence thresholding of the EP signal in frequency domain in which energy distribution of the EP signal is usually not uniform. The suggested technique is coupled with the conventional bispectrum estimation technique such as least square method and recursive method. Some results with simulated data and real EP signal are shown.

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Laguerre 모델을 이용한 미지 시스템의 온-라인 시스템 동정에 관한 연구 (A Study the On-Line Systems Identification of Unknown Systems using Laguerre Models)

  • 오현철;김윤상;이재춘;안두수
    • 대한전기학회논문지:전력기술부문A
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    • 제48권6호
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    • pp.728-734
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    • 1999
  • An on-line system identification scheme of unknown system is proposed based on a Laguerre models representation. The unknown parameters are detemined using recursive least-square identification. The proposed method have the advantage that an unknown system can be modelled without structural knowledge and assumption about the true model order and time delay. Therefore, the proposed method can make the design procedure very when compared to widely-used conventional method.

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전력 계통 안정화 제어를 위한 이산시간 제어기 설계 (A Study on digital Controller for Power System Stabilization)

  • 박영문;현승호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1992년도 하계학술대회 논문집 A
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    • pp.135-137
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    • 1992
  • A new algorithm for self-tuning digital controller is proposed. The system to be controlled is identified on line in auto-regressive-moving-average(ARMA) form via recursive least mean square method. The control law is obtained from the minimization of an objective function. The proposed objective function is similar to that of Generalized Minimum Variance(GMV) method but modified to lessen the overshoot and to avoid numerical divergence problem. This algorithm is applied to the power system stabilization and the comparison of the proposed method with a conventional power system stabilizer(PSS) is presented.

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Leak detection in a pipeline based on estimation theory

  • Jeong, Sang-Hun;Bang, Sung-Ho;Lee, Kwang-Soon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.170-175
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    • 1992
  • A leak detection method for diagnosis of the leak position in a pipeline was developed using an estimation theory with the assumption that the measured flow rates and pressures are stochastic processes. A notch filter was designed using power spectral density analysis of measurements to reduce the effects of disturbances. The noise model dimension was determined by hypothesis testing and then recursive extended least square method was applied to estimate the leak position in real time. The proposed method was applied to an experimental system for evaluation of its performance.

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신경망 회로를 이용한 레이저 간섭계의 적응형 오차보정 (Adaptive Nonlinearity Compensation in Laser Interferometer using Neural Network)

  • 허건행;이우람;유관호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.86-88
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    • 2007
  • In the semiconductor manufacturing industry, the heterodyne laser interferometer plays as an ultra-precise measurement system. However, the heterodyne laser interferometer has some unwanted nonlinearity error which is caused from frequency-mixing. This is an obstacle to improve the measurement accuracy in nanometer scale. In this paper we propose a compensation algorithm based on RLS(recursive least square) method and artificial intelligence method, which reduce the nonlinearity error in the heterodyne laser interferometer. With the capacitance displacement sensor we get a reference signal which can be transformed into the intensity domain. Using the back-propagation Neural Network method, we train the network to track the reference signal. Through some experiments, we demonstrate the effectiveness of the proposed algorithm in measurement accuracy.

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NEW ADAPTIVE METHOD FOR VOLTAGE SAG AND SWELL DETECTION

  • Mohamed, Mansour A.
    • 한국융합학회논문지
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    • 제4권1호
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    • pp.33-41
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    • 2013
  • This paper presents an adaptive recursive least squares algorithm (ARLS) for detecting voltage sag and voltage swell events in power systems. Different methods have been developed to detect voltage sag and voltage swell. Some of them use window techniques, which are too slow when voltage sag or swell mitigation is required. Others depend on the extraction of a single non-stationary sinusoidal signal out of a given multi-components input signal, and therefore they don't consider the harmonic components in calculating the voltage root mean square value (rms). The method, proposed in this paper, is capable of estimating the voltage rms taking into account all harmonic components. The method is tested by applying it to different, simulated signals using ATP program, and compared with voltage sag detection algorithms.