• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.525-525
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• 2000

In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

• 한국국방경영분석학회지
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• 제13권1호
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• pp.1-18
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• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.706-712
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• 2006

Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

• 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.

• 대한기계학회논문집
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• 제9권5호
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• pp.590-597
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• 1985

본 논문에서는 위치오차는 가공전 밀링베드를 수치제어 장치를 이용하여 가공 면에 수직한 방향으로 움직여 수치제어 장치인 스텝모우터의 분해능 한계 내에서 보정 하고 또한 공구휨에 상당하는 만큼 이 송속도를 더함으로써 제어하며, 파형오차는 이 송속도와 공구처짐 사이의 관계를 수정된 Taylor의 공구식으로 모형화하고 절삭공정중 이송속도를 적절히 조절하여 공구의 휨양을 제어함으로써 스텝모우터를 갖는 밀링머시 인에서 길이 508mm,두께 20mm의 두꺼운 철판을 평면절삭하는 경우 직진도오차를 최소 로 하는 GAC 방법을 개발하였다.측정은 밀링머시인 자체의 구조적, 동적변화나 절삭 조건의 변화, 공구의 재질 및 마멸상태의 변화, 공작물의 재질 변화등에 적응할 수 있 도록 Fig. 2에 보인 바와 같이 등간격으로 배열된 100개의 위치에서 가공후(post-pro- cess)측정을 통하여 취하였고, 절삭계수의 추정은 측정점을 각각 10개씩 10개의 구간 으로 묶어 각 구간에서의 계의 특성이 변하지 않는다는 가정하에서 계수를 지수가중 반복최소 자승(exponentially weighted recursive least squares, EWRLS)법을 이용하 여 추정하였고, 실제 절삭작업중 모델의 계수변화에 대한 사전 지식이 없이도 이들 계 수들을 보정시킴으로써 최적의 직진도를 얻을 수 있는 절삭조건을 제시하였다. 그리 고 이 방법의 도입으로 단일(SINGLE-PASS)밀링작업이 가능함을 보였고 또한 방법의 타 당성을 증명하기 위하여 여러 경우의 절삭상태에서 실험을 수행하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 추계학술대회 논문집
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• pp.200-201
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• 2013

This paper investigates a new approach for Li-Ion battery state-of-charge (SOC) estimation using sliding mode observer (SMO) technique including parameters aging compensation via recursive least squares (RLS). The main advantages of this approach would be low computational load, easiness of implementation along with the robustness of the method for internal battery model parameters estimation. The proposed algorithm was first tested on a set of acquired battery data using implementation in Simulink and later developed as C-code module for firmware application.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1992년도 추계학술발표회논문집
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• pp.56-59
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• 1992

Adaptive active attenuation of noise in a duct is considered. A duct is modelled when the acoustic feedback exists. The secondary path transfer function is estimated using multiple model approaches. An IIR structure is assumed for the control filter, and the recursive least mean squares algorithm is used to adjust the filter coefficients.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.31-39
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• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.161-165
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• 1992

The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.