• Communications for Statistical Applications and Methods
• /
• v.21 no.4
• /
• pp.335-347
• /
• 2014

This paper employs dynamic conditional correlation (DCC) model to examine time-varying comovement in the Korean stock market with a focus on the financial industry. Analyzing the daily returns of KOSPI 200 eight sector indices from January 2008 to December 2013, we find that stock market correlations significantly increased during the GFC period. The Financial Sector had the highest correlation between the Constructions-Machinery Sector; however, the Consumer Discretionary and Consumer Staples sectors indicated a relatively lower correlation between the Financial Sector. In terms of model fitting, the DCC with t distribution model concludes as the best among the four alternatives based on BIC, and the estimated shape parameter of t distribution is less than 10, implicating a strong tail dependence between the sectors. We report little asymmetric effect in correlation dynamics between sectors; however, we find strong asymmetric effect in volatility dynamics for each sector return.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.4
• /
• pp.48-53
• /
• 2013

In general, the LLC resonant topology consists of three stages as; square wave generator, resonant network, and rectifier network. LLC resonant converter has the time slowly varying parameters. However, the power LEDs as the load of LLC converter can be regarded as fast time varying parameters. In this paper, the mathematical model of half-bridge resonant converter including with the power LEDs is introduced for the current controller design model. Using this controller design model, the parameter adaptive output feedback controller will be designed to control the power LEDs current. In order to show the validities of the proposed model, the parameter adaptive output feedback controller, the experimental investigation will be presented.

• Coupled systems mechanics
• /
• v.13 no.1
• /
• pp.73-93
• /
• 2024

In this work, we propose combining an advanced optimal control algorithm with a geometrically exact beam model. For simplicity, the 2D Reissner beam model is chosen to represent large displacements and rotations. The difficulty pertains to the nonlinear nature of beam kinematics affecting the tangent stiffness matrix, making it non-constant, which compromises direct use of optimal control methods for linear problems. Thus, we seek to accommodate a time varying control using linear-quadratic regulator (LQR) algorithm with the proposed geometrically nonlinear beam model. We provide a detailed theoretical formulation and its numerical implementation in a variational format form. Several illustrative numerical examples are provided to confirm an excellent performance of the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.87.2-87
• /
• 2001

By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is an uncertain time-variant system. Control synthesis based on a reduced design model is a combined ...

• The Transactions of the Korean Institute of Power Electronics
• /
• v.20 no.6
• /
• pp.498-508
• /
• 2015

In the simulation of photovoltaic (PV) power conditioning systems, PSIM is a widely accepted circuit simulation platform because of its fast speed and C-code support. PSIM provides two kinds of generic PV panel models: functional model and physical model. Whereas the functional model simulates PV in the standard test condition (STC) only, the physical model can emulate changing PV characteristics under varying temperatures and irradiation conditions and is thus more suitable for system simulation. However, the physical model requires complicated parameters from users, and thus it is prone to errors and is difficult to use. In this study, a new PSIM model for PV is presented to solve these problems. The proposed model utilizes manufacturers' datasheet values specified under STC only and excludes user-defined information from input parameters. To achieve good accuracy even in varying environmental conditions, single-diode model parameters are successively tuned to a time-varying virtual datasheet. Comparison with a conventional physical model shows that the proposed model provides more accurate simulation according to error analysis based on the EN50530 standard.

• Industrial Engineering and Management Systems
• /
• v.12 no.1
• /
• pp.23-29
• /
• 2013

This paper presents inventory models for fresh agriculture products with time-varying deterioration rate. Due to the particularity of fresh agriculture products, the demand rate is a function that depends on sale price and freshness. The deterioration rate increases with time and is assumed to be a time-varying function. In the models, the inventory cycle may be constant or variable. The optimal solutions of models are discussed for different freshness and the deterioration rate. The results of experiments show that the profit depends on the freshness and deterioration rate of products. With the increasing inventory cycle, the sale price and profit increase at first and then start decreasing. Furthermore, when the inventory cycle is variable, the total profit is a binary function of the sale price and inventory cycle. There exist unique sale price and inventory cycle such that the profit is optimal. The results also show that the optimal sale price and inventory cycle depend on the freshness and the deterioration rate of fresh agriculture products.

• Proceedings of the KIEE Conference
• /
• 2002.11c
• /
• pp.54-57
• /
• 2002

In this paper model reference adaptive control (MRAC) of linear time-varying(LTV) systems is considered. MRAC for a linear time invariant(LTI) system does not assure the boundedness of the output and parameter estimation errors in the presence of time variations of the parameters. However, changing the adaptive laws such as use of $\sigma$-modification can result in the boundedness of the output and parameter estimation errors[5]. Together with the $\sigma$-modification in the adaptive law, we also modify the control law by adding an additional term to the standard control law. The additional term leads to smaller bounds of the output and parameter estimation errors when compared to the case where only the standard control law is applied.

• Journal of the Korean Society of Safety
• /
• v.21 no.4 s.76
• /
• pp.25-32
• /
• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.2
• /
• pp.227-234
• /
• 1996

The discount survival model is proposed for the application of the Cox model on the analysis of survival data with time-varying effects of covariates. Algorithms for the recursive estimation of the parameter vector and the retrospective estimation of the survival function are suggested. Also the algorithm of forecasting of the survival function of individuals of specific covariates in the next time interval based on the information gathered until the end of a certain time interval is suggested.

• Journal of the Korean Statistical Society
• /
• v.33 no.4
• /
• pp.367-379
• /
• 2004

This article deals with the nonparametric analysis of longitudinal data when there exist possible correlations among repeated measurements for a given subject. We consider a quasi-likelihood regression model where a transformation of the regression function through a link function is linear in time-varying coefficients. We investigate the local polynomial approach to estimate the time-varying coefficients, and derive the asymptotic distribution of the estimators in this quasi-likelihood context. A real data set is analyzed as an illustrative example.