• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.925-932
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• 2012

The article introduces a method to estimate a cointegrated vector autoregressive model, using mixed-frequency data, in terms of a state-space representation of the vector error correction(VECM) of the model. The method directly estimates the parameters of the model, in a state-space form of its VECM representation, using the available data in its mixed-frequency form. Then it allows one to compute in-sample smoothed estimates and out-of-sample forecasts at their high-frequency intervals using the estimated model. The method is applied to a mixed-frequency data set that consists of the quarterly real gross domestic product and three monthly coincident indicators. The result shows that the method produces accurate smoothed and forecasted estimates in comparison to a method based on single-frequency data.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.255-261
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• 2021

This paper proposes impedance-based stability analysis of DC-DC boost converters, where a harmonic state space (HSS) modeling technique is used. At first, the HSS model of the boost converter is developed. Then, the closed-loop output impedance of the converter is derived in frequency domain using small signal modeling including frequency couplings, where harmonic transfer function (HTF) matrices of the open-loop output impedance, the duty-to-output, and the voltage controller are involved. The frequency response of the output impedance reveals a resonance frequency at low frequency region and frequency couplings at sidebands of switching frequency which agree with the simulation and experimental result.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.57-62
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• 2023

In this review, we introduce the non-parametric Bayesian filtering algorithm known as the point-mass filter (PMF) and discuss recent studies related to it. PMF realizes Bayesian filtering by placing a deterministic grid on the state space and calculating the probability density at each grid point. PMF is known for its robustness and high accuracy compared to other nonparametric Bayesian filtering algorithms due to its uniform sampling. However, a drawback of PMF is its inherently high computational complexity in the prediction phase. In this review, we aim to understand the principles of the PMF algorithm and the reasons for the high computational complexity, and summarize recent research efforts to overcome this challenge. We hope that this review contributes to encouraging the consideration of PMF applications for various systems.

• Communications of the Korean Mathematical Society
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• v.20 no.2
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• pp.381-393
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• 2005

We consider a type of large deviation principle obtained by Freidlin and Wentzell for the solution of Stochastic differential equations in a conuclear space. We are using exponential tail estimates and exit probability of a Ito process. The nuclear structure of the state space is also used.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1054-1061
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• 2003

Q-Learning, a representative algorithm of reinforcement learning, experiences repeatedly until estimation values about all state-action pairs of state space converge and achieve optimal policies. When the state space is high dimensional or continuous, complex reinforcement learning tasks involve very large state space and suffer from storing all individual state values in a single table. We introduce Q-Map that is new function approximation method to get classified policies. As an agent learns on-line, Q-Map groups states of similar situations and adapts to new experiences repeatedly. State-action pairs necessary for fine control are treated in the form of rule. As a result of experiment in maze environment and mountain car problem, we can achieve classified knowledge and extract easily rules from Q-Map

• Journal of the Korean earth science society
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• v.31 no.3
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• pp.259-266
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• 2010

High school students' understanding hierarchy of astronomical concepts and an individual student's knowledge state are analyzed by using the knowledge space theory that allows one to infer an individual's entire knowledge on a subject based on fragmentary information coming from that student's answers. The hierarchy of astronomical space concepts is: spatial position$\ll$spatial reasoning$\ll$spatial variation. In addition, an analysis of assessment materials using the knowledge space theory shows not only the relationship of assessment questions but also the knowledge state of individual students, which the current evaluation method is not able to reveal. Therefore, the assessment analysis of this study using the knowledge space theory becomes critically instrumental in providing information of an instructional differentiation amenable to individual learners for deciding their level of understanding and selecting suitable curriculum.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.368-376
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• 2007

How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.387-396
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• 2009

The life and performance of lithium battery are greatly influenced by the formation process which is essential in the process of manufacture. Charge/discharge system for the lithium battery are required for the formation process. To simulate such a system in a conventional method takes very long time and requires huge memory space to save data files. So the simulation may be impossible with a general-purpose PC. In this paper, the lithium battery is modelled to a resistor-capacitor serial circuit and the lithium battery charge/discharge system is analyzed and simulated by using state space averaging method. As a result, the simulation time is reduced dramatically and the simulation of the lithium battery charge/discharge system becomes possible on a general-purpose PC within 3 hours. Also, both the charge/discharge characteristics and the time required to charge/discharge of the lithium battery charge/discharge system can be observed. To verify the propriety of resistor-capacitor serial circuit modeling method for lithium battery and the validity of the analysis and simulation based on state space averaging, the lithium battery charge/discharge system is composed and experimentations are carried out.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2606-2611
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• 2003

Comprehensive study on the control system design for a RTP process has been conducted. The purpose of the control system is to maintain maximum temperature uniformity across the silicon wafer achieving precise tracking for various reference trajectories. The study has been carried out in two stages: thermal balance modeling on the basis of a semi-empirical radiation model, and optimal iterative learning controller design on the basis of a linear state space model. First, we found through steady state radiation modeling that the fourth power of wafer temperatures, lamp powers, and the fourth power of chamber wall temperature are related by an emissivity-independent linear equation. Next, for control of the MIMO system, a state space modeland LQG-based two-stage batch control technique was derived and employed to reduce the heavy computational demand in the original two-stage batch control technique. By accommodating the first result, a linear state space model for the controller design was identified between the lamp powers and the fourth power of wafer temperatures as inputs and outputs, respectively. The control system was applied to an experimental RTP equipment. As a consequence, great uniformity improvement could be attained over the entire time horizon compared to the original multi-loop PID control. In addition, controller implementation was standardized and facilitated by completely eliminating the tedious and lengthy control tuning trial.