• 한국자동차공학회논문집
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• 제17권1호
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• pp.130-136
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• 2009

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of Li-ion battery indicates highly dependant of temperatures. The system pole and internal resistance changes 6.6 and 18 times at $-20^{\circ}C$, comparing with those at $25^{\circ}C$, respectively. These results will be utilized on constructing model-based state observer or an on-line identification and an adaptation of the model parameters in battery management systems for hybrid electric vehicle applications.

• 한국음향학회지
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• 제14권3호
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• pp.37-48
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• 1995

일반화된 완전최소자승법 (generalized total least squares method, GTLS)의 ARMA 시스템 식별에의 적용과 GTLS의 적응알고리듬에 대하여 논한다. 일반화된 완전최소자승법은 일별과 출력을 알고 있는 시스템식별 (system identification)문제에서, 출력이 잡음에 의하여 오염된 경우, 편이되지 않은 해를 구하기 위하여 사용되는 방법이다. 본 논문에서는 먼저 GTLS를 ARMA 시스템 식별에 적용하기 위한 formulation을 하고, 일반화된 완전최소자승법의 일반 해의 성질과 역행렬 정리 (matrix inverse lemma)를 이용하여 적응 GTLS 방법을 제안한다. 다음 제안된 방법을 통하여 시스템식별에 적용하여 그 성능을 평가한다. 또한 GTLS 알고리듬과 제안한 적응 GTLS 알고리듬의 성능을 수학적으로 해석하고 컴퓨터 시뮬레이션을 통하여 이를 검증한다.

• Wind and Structures
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• 제11권1호
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• pp.19-33
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• 2008

This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

• 대한의용생체공학회:의공학회지
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• 제26권2호
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• pp.87-93
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• 2005

A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

• 한국생산제조학회지
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• 제8권3호
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• 전기학회논문지
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• 제60권8호
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• pp.1510-1514
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• 2011

In this paper, linear discrete model of the electro-hydraulic servo system are made for parameters estimation. The parameters of electro-hydraulic servo system are estimated using the recursive least square method. Persistent excitation conditions are studied in order to estimate parameters of electro-hydraulic servo system to real values and parameters estimation affections are studied due to the forgetting factors variation. As the results, An parameter estimation method has been synthesized for minimizing the error between reference and error.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.984-990
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• 2013

This paper develops a new Intelligent Electronic Device (IED), and then presents an application method of a monthly load forecasting algorithm on the smart IEDs. A Multiple Linear Regression (MLR) model implemented with Recursive Least Square (RLS) estimation is established in the algorithm. Case Study proves the accuracy and reliability of this algorithm and demonstrates the practical meanings through designed screens. The application method shows the general way to make use of IED's smart characteristics and thereby reveals a broad prospect of smart function realization in application.

• 대한전자공학회논문지TE
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• 제39권4호
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• pp.414-422
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• 2002

본 논문에서는 적응 제어 문제를 다루기 위해 CFCM 클러스터링과 퍼지 균등화 기법을 이용하여 새로운 적응 뉴로-퍼지 제어기를 설계하고자 한다. 먼저 오프라인에서 CFCM은 입력데이터의 성질과 출력 패턴의 성질까지도 고려한 퍼지 클러스터링 기법으로 적응 뉴로-퍼지 제어기의 구조동정을 수행한다. 파라미터 동정은 역전과 알고리즘과 RLSE(Recursive Least Square Estimate)을 이용한 하이브리드 학습을 수행한다. 온라인 학습에서는 시변특성으로 인해 전제부 및 결론부 파라미터를 실시간으로 계산된다. 시뮬레이션으로 온 라인 적응 뉴로-퍼지 제어 시스템의 성능을 입증하기 위해 목욕물 온도제어 시스템에 대해 다루고 전형적인 퍼지 제어기에 비해 오프 라인과 온 라인 설계 모두 좋은 성능을 보이고자 한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• 한국통신학회논문지
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• 제34권5C호
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• pp.521-526
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• 2009

In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.