• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• 대한전자공학회논문지
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• 제24권2호
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• pp.280-291
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• 1987

In this paper, the linear autoregressive model of EMG signal for four basic arm functions was presented and parameters for each function were estimated. The signal identification was carried out using function discrimination algorithm. It was validated that EMG signal was a widesense stationary process and the linear autoregressive model of EMG signal was constructed through approximating it to Gaussian process. It was confined that Levinson-Durbin algoridthm is a more appropriate one than the recursive least square method for parameter estimation of the linear model. Optimal function discrimination was acquired when sampling frequency was 500Hz and two electrodes were attached to bicep and tricep muscle, respectively. Parameter values were independent of variance and the number of minimum data for function discrimination was 200. Bayesian discrimination method turned out to be a better one than parallel filtering method for functional discrimination recognition.

• Communications for Statistical Applications and Methods
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• 제25권1호
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.

• 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.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권1호
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• pp.1-7
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• 2002

This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

• 자동차안전학회지
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• 제16권2호
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• pp.51-59
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• 2024

This study presents a method for health monitoring of rotating objects for mobility based on multiple recursive least squares(RLS) algorithms. The performance degradation of the rotating objects causes low handing / low driving performances and even fatal accidents. Therefore, health monitoring algorithm of rotating objects is one of the important technologies for mobility fail-safe and maintenance areas. In order for health monitoring of rotating objects, four recursive least squares algorithms with forgetting factor were designed in this study. The health monitoring algorithm proposed in this study consists of two steps such as uncertainty estimation and parameter changes estimation. In order to improve estimation accuracy, time delay function was applied to the estimated signals based on the first order differential equation and forgetting factors used for the RLS were reasonably tuned. The health monitoring algorithm was constructed in Matlab/Simulink environment and simulation-based performance evaluation was conducted using DC motor model. The evaluation results showed that the proposed algorithm estimates the actual parameter differences reasonably using velocity and current information.

• 응용통계연구
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• 제24권6호
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• pp.1197-1211
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• 2011

The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.

• 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.

• 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.

• 동력기계공학회지
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• 제9권4호
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.