• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.465-470
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• 2003

In this study, the state-space Newmark method based on average velocity is presented to analyse the transient dynamic response for general dynamic system. The conventional Newmark method based on average acceleration cannot he directly to the first-order state-space differential equations introducing the state-space vector. To overcome this problem, the time-step integration algorithm, based on average velocity concept, suitable for the first-order state-space differential equations is proposed In results, the proposed method has %he numerical stability and order of accuracy, which is proved analytically, equal to those of the conventional Newmark method based on average acceleration. Also, the formulation for numerical solution is very simple and the calculation time Is nearly equal to that of the conventional Newmark method based on average acceleration in spite of an increase of two times over matrix size. This method will be look forward to applying the general dynamic system to calculate the transient dynamic response.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.5
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• pp.424-431
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• 2004

An implicit direct-time integration method for obtaining transient responses of general dynamic systems is described. The conventional Newmark method cannot be directly applied to state-space first-order differential equations, which contain no explicit acceleration terms. The method proposed here is the state-space Newmark method that incorporates the average velocity concept, and can be applied to an analysis of general dynamic systems that are expressed by state-space first-order differential equations. It is also readily coded into a program. Stability and accuracy analyses indicate that the method is numerically unconditionally stable like the conventional Newmark method, and has a period error of 2nd-order accuracy for small damping and 4th-order for large damping and an amplitude error of 2nd-order, regardless of damping. In addition, its utility and validity are confirmed by two application examples. The results suggest that the proposed state-space Newmark method based on average velocity be generally applied to the analysis of transient responses of general dynamic systems with a high degree of reliability with respect to stability and accuracy.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.4
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• pp.186-192
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• 2002

In this paper, interleaved boost power factor corrector(IBPFC) is applied as a pre-regulator in switch mode power supply. IBPFC can reduce input current ripple and effectively increase the switching frequency without increasing the switching losses, because input current is divided each 50% by two switching devices. IBPFC can be classified as three cases by duty ratio condition in continuous current mode and be carried out state space average modeling. According to the modeling, steady and transient state analysis is performed by steady elements and perturbation element. Control transfer function is derived for design of control system.

• Journal of Power Electronics
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• v.12 no.3
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• pp.410-417
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• 2012

In this paper, a direct current control method based on a one-cycle controller (DCOCC) for double frequency buck converters (DF buck) is proposed. This control method can make the average current through the high frequency and low frequency inductors of a DF buck converter equal. This is similar to the average current control method. However, the design of the loop compensator is much easier when compared with the average current control. Since the average current though the high frequency and low frequency inductors is equivalent, the current stress of the high frequency switches and the switch losses are minimized. Therefore, the efficiency of the DF buck converter is improved. Firstly, the operation principle of DCOCC is described, then the small signal models of a one cycle controller and a DF buck converter are presented based on the state space average method. Eventually, a system block diagram of the DCOCC controlled DF buck is established and the compensator is designed. Finally, simulation and experiment results are given to verify the correction of the theory analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.151-157
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• 1992

This paper presents a method for analyzing the transfer lines with finite storage buffers. Each machine spends a random amount of time processing each material. This transfer line can be modeled by the tandem queueing system with finite buffers. The great dimensionality of the state space renders the analysis of such system a formidable task. We propose an efficient algorithm to obtain the marginal state probabilities based on the exact algorithm for the two-machine system. Other performance measures, such as the utilization, the blocking probability, the average sojourn time, and the average queue length, can be easily calculated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.107-114
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• 1995

The objective of this study is to design a one-stage dynamic prediction model with Kalman state space model. For a model verification, it is compared with EWMA(Exponentially Weighed Moving Average) model. The model designed in this research can be extended to process prevention control and quality monitoring.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.349-356
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• 1994

The purpose of this study is to develop a linear reservoir model with Kalman filter using Kalman filter theory which removes a physical uncertainty of :ainfall-runoff process. A linear reservoir model, which is the basic model of Kalman filter, is used to calculate runoff from rainfall in river basin. A linear reservoir model with Kalman filter is composed of a state-space model using a system model and a observation model. The state-vector of system model in linear. The average value of the ordinate of IUH for a linear reservoir model with Kalman filter is used as the initial value of state-vector. A .linear reservoir model with Kalman filter shows better results than those by linear reserevoir model, and decreases a physical uncertainty of rainfall-runoff process in river basin.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.1-8
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• 2019

In this paper, we propose a performance isolation of shared space for virtualized SSD based storage systems, to solve the weakness in a VSSD framework. The proposed scheme adopts a CFQ scheduler and a shared space-based FTL for the fairness and the performance isolation for multiple users on virtualized SSD based storage systems. Using the CFQ scheduler, we ensure SLOs for the storage systems such as a service time, a allocated space, and a IO latency for users on the virtualized storage systems. In addition, to improve a throughput and reduce a computational latency for garbage collection, a shared space-based FTL is adopted to maintain the information of SLOs for users and it manages shared spaces among the users. In our experiments, the proposal improved the throughput of garbage collection by 7.11%, on average, and reduced the computational latency for garbage collection by 9.63% on average, compared to the previous work.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.152-154
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• 2009

태양광발전 시스템에서 사용되는 컨버터는 기존의 입출력 관계로 모델링할 수 없다. 이는 태양광 전지를 컨버터의 입력단으로 사용하여, 모델의 입력 전류와 전압이 수시로 변동하기 때문이다. 이런 오류가 있는 방법으로 모델링하여 설계한 제어기가 좋은 성능을 내기는 어렵다. 본 논문에서는 기존의 입출력 관계를 반대로 한 벅 컨버터의 새로운 모델을 제시한다. 모델링은 상태공간평균화 방법(State-Space Averaging Method)을 사용하였다.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.143-154
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• 2024

This paper considers a combined model of exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models that are commonly used to forecast time series data. The combined model is constructed through an innovational state space model based on the level variable instead of the differenced variable, and the identifiability of the model is investigated. We consider the maximum likelihood estimation for the model parameters and suggest the model selection steps. The forecasting performance of the model is evaluated by two real time series data. We consider the three competing models; ETS, ARIMA and the trigonometric Box-Cox autoregressive and moving average trend seasonal (TBATS) models, and compare and evaluate their root mean squared errors and mean absolute percentage errors for accuracy. The results show that the combined model outperforms the competing models.