• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.95-104
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• 2020

In financial economics studies, the autoregressive model has been a workhorse for a long time. However, the model has a fixed value on every parameter and requires the stationarity assumptions. Time-varying coefficient autoregressive model that we use in this paper offers some desirable benefits over the traditional model such as the parameters are allowed to be varied over-time and can be applies to non-stationary financial data. This paper provides the Monte Carlo simulation studies which show that the model can capture the dynamic movement of parameters very well, even though, there are some sudden changes or jumps. For the daily data from January 1, 2015 to February 12, 2020, our paper provides the empirical studies that Thailand, Taiwan and Tokyo Stock market Index can be explained very well by the time-varying coefficient autoregressive model with lag order one while South Korea's stock index can be explained by the model with lag order three. We show that the model can unveil the non-linear shape of the estimated mean. We employ GJR-GARCH in the condition variance equation and found the evidences that the negative shocks have more impact on market's volatility than the positive shock in the case of South Korea and Tokyo.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.402-406
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• 1990

A new approach of a time-varying switching hyperplane based on the theory of variable structure system (VSS) is proposed for the control of multivariable systems. While the conventional switching surface can net achieve the robust performance against parameter variations and disturbances before the sliding mode occurs, the proposed switching hyperplane, which is obtained from the eigen-structure assignment theory powerfully used in the linear multivariable systems, ensures the sliding mode from the initial state. And new continuous control input which guarantees the sliding mode is proposed. This new control input does not arise chattering problem which arises with the conventional control input of variable structure control systems. Through numerical examples, the expellant performances of the proposed controller are verified.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.53-59
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• 2022

This paper describes an integrated control of torque vectoring and rear wheel steering using model predictive control. The control objective is to minimize the yaw rate and body side slip angle errors with chattering alleviation. The proposed model predictive controller is devised using a linear parameter-varying (LPV) vehicle model with real time estimation of the varying model parameters. The proposed controller has been investigated via computer simulations. In the simulation results, the performance of the proposed controller has been compared with uncontrolled cases. The simulation results show that the proposed algorithm can improve the lateral stability and handling performance.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.886-892
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• 2013

Hydraulic hose assemblies are used as piping components for construction machinery, automobile, aircraft, industrial machinery, machine tools, and machinery for ships. Then the reliability of hose assemblies is important because total hydraulic system, which used to deliver the fluid power ($P^*Q$) needed to flexibility in the piping system, is not operated if the hose assembly failed in the system. The data of the accelerated life test estimated through the shape parameter(${\beta}$) resulting of the Weibull distribution analysis. This study has tried to reduce the test time resulting from varying impulse pressure range and the flexing diameter. Accelerated life test model for the test results was adopted the GLL(generalized log linear) and the accelerated indexes are identified as 6.64 for the pressure and 4.46 for flexing radius. Also, it found that shape parameter is 6.19, scale parameter(${\eta}$) is $1.035{\times}108$, which were adopted the pressure 35 MPa and the flexing diameter R100 mm in the used condition.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.62-74
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• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.167-175
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• 2001

This paper presents design of active roll controller of a vehicle and experimental study using the electric actuating roll control system. Firstly, parameter sensitivity analysis is performed based on 3DOF linear vehicle model. The controller is designed in the frame work of gain-scheduled H$\infty$ control scheme considering the varying parameters induced by laden and running vehicle condition. In order to investigate a feasibility of an active control system, experimental work is performed using hardware-in-the -loop setup which has been constructed by the devised electric actuating system and the full vehicle model with tire characteristics. The performance is evaluated by experiment using hardware-in-the -loop simulation under the conditions of some steer maneuvers and parameter variations.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1212-1220
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• 2015

This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.277-288
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• 1997

For the analysis of survival data including covariates whose effects vary in time, the multiprocess discount survival model is proposed. The parameter vector modeling the time-varying effects of covariates is to vary between time intervals and its evolution between time intervals depends on the perturbation of the next time interval. The recursive estimation of the parameter vector can be obtained at the end of each time interval. The retrospective estimation of the survival function and the forecasting of the survival function of individuals of the specific covariates also can be obtained based on the information gathered until the end of the time interval.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1997.11a
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• pp.85-89
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• 1997

A microstructure of realistic ZnO varistor was constructed by Voronoi network and studied cia computer simulation. The grain size and standard deviation was calculated with new method and have good agreement with experimental data. In this network, the grain boundary conditions of three different type are randomly distributed. The three electrical boundary conditions . (1) type A junctions (high nonlinearity); (2) type B junctions (low nonlinearity); (3) type C junctions (linear with low-resistivity) are fitted from the experimental measurement. The electrical properties were studied by varying the boundary type concentration and the disorder parameter d. The shape of I-V characteristic curve of the network is affected by the type concentration and the disorder parameter has an effect on the double inflected region.