• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.1
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• pp.36-45
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• 1998

A simple source voltage clamped resonant link (SVCRL) inverter is proposed to clamp the DC link voltage to the input source voltage and reduce the current rating of resonant inductor. The current control of a permanent magnet synchronous motor (PMSM) using a predictive current control technique (PCCT) employing the SVCRL inverter is also investigated to overcome the disadvantage of the current regulated delta modulation (CRDM) control technique. By using the PCCT based on the discrete model of a PMSM and estimation of back EMF, the minimized current ripple with small number of switchings can be obtained. Finally, the comparative computer simulation and experimental results are given to show the usefulness of the proposed technique.

• Journal of Environmental Science International
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• v.25 no.8
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• pp.1107-1114
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• 2016

This research, sponsored by the Korean Ministry of Environment in 2014, was the first epidemiological study in Korea that investigated the health impact assessment of radon exposure. Its purpose was to construct a model that calculated the annual mean cumulative radon exposure concentrations, so that reliable conclusions could be drawn from environment-control group research. Radon causes chronic lung cancer. Therefore, the long-term measurement of radon exposure concentration, over one year, is needed in order to develop a health impact assessment for radon. Hence, based on the seasonal correction model suggested by Pinel et al.(1995), a predictive model of annual mean radon concentration was developed using the year-long seasonal measurement data from the National Institute of Environmental Research, the Korea Institute of Nuclear Safety, the Hanyang University Outdoor Radon Concentration Observatory, and the results from a 3-month (one season) survey, which is the official test method for radon measurement designated by the Korean Ministry of Environment. In addition, a model for evaluating the effective annual dose for radon was developed, using dosimetric methods. The model took into account the predictive model for annual mean radon concentrations and the activity characteristics of the residents.

• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.365-375
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• 2024

Diverse methods to evaluate the prediction model of a time to event have been proposed in the context of right censored data where all subjects are subject to be susceptible. A time-dependent AUC (area under curve) measures the predictive ability of a marker based on case group and control one which are varying over time. When a substantial portion of subjects are event-free, a population consists of a susceptible group and a cured one. An uncertain curability of censored subjects makes it difficult to define both case group and control one. In this paper, our goal is to propose a time-dependent AUC for a cure rate model when a censoring distribution is related with covariates. A class of inverse probability of censoring weighted (IPCW) AUC estimators is proposed to adjust the possible sampling bias. We evaluate the finite sample performance of the suggested methods with diverse simulation schemes and the application to the melanoma dataset is presented to compare with other methods.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.280-285
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• 2004

This paper is concerned with the modeling and identification of sequencing batch reactor (SBR) via genetic algorithm based polynomial neural network (GA-based PNN). The model describes a biological SBR used in the wastewater treatment process fur nitrogen removal. A conventional polynomial neural network (PNN) is applied to construct a predictive model of SBR process fur nitrogen removal before. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables and type (order) of the polynomials to each node. They must be fixed by the designer in advance before the architecture is constructed. So the trial and error method must go with heavy computation burden and low efficiency. To alleviate these problems, we propose GA-based PNN. The order of the polynomial, the number of input variables, and the optimum input variables are encoded as a chromosome and fitness of each chromosome is computed. Simulation results have shown that the complex SBR process can be modeled reasonably well by the present scheme with a much simpler structure compared with the conventional PNN model.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.333-336
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• 1992

In this paper, We propose a PID-type of self-tuning algorithm which is based on the parameter estimation and the minimization of the cost function. We use the CARIMA model for parameter estimation and determine the discrete PID controller parameters by minimizing the cost function which considers the quadratic deviations of the predicted output over the set-point as well as the control efforts. Also, The algorithm is extended by incorporating constraints of the control signal. Simulations are performed to illustrate the efficiency of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.766-771
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• 1997

In this strip casting,size of the roll separating force is a index representing the solidifying status of the melt. Rolling forces at the start of the casting process can change abruptly due to the overcooling of the leader strip. This inconsistensy leads to machine damage or deficient solidification which results in the failure of the casting. In this study, a mathematical model is derived for the hydraulic servo pressure control system for the twin roll strip caster and its parameters are estimated by the RLS algorithm. Based on the identified model, an one-step ahead predictive control method is applied in order to minimize the transient fluctuation of the rolling force. Its simulation results are compared with those of the conventional PI controllers.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.1.2-6
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• 1994

A state or the arts in Japanese chemical process control is reviewed based on experience in applying advanced process control schemes to several industrial chemical processes. The applications validate model predictive control (MPC), the most popular advanced control scheme in the process control community, as, indeed, a powerful and practical control algorithm. However, at the same time, it is elucidated that MPC can solve only the control algorithm part of the problem and one needs chemical and systems engineering aspects to solve the entire problem. By illustrating several industrial process control problems, the need for chemical engineering aspects as well as the future direction for process control are addressed, especially in light or current attitudes toward product quality.

• Journal of Drive and Control
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• v.13 no.4
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• pp.59-67
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• 2016

This paper proposes a model-prediction-based collision-avoidance algorithm for excavators for which the recursive-least-squares (RLS) estimation of the excavator's rotational inertia is used. To estimate the rotational inertia of the excavator, the RLS estimation with multiple forgetting and two updating rules for the nominal parameter and the forgetting factors was conducted based on the excavator-swing dynamics. The average value of the estimated rotational inertia that is for the minimizing effects of the estimation error was computed using the recursive-average method with forgetting. Based on the swing dynamics, the computed average of the rotational inertia, the damping coefficient for braking, and the excavator's braking angle were predicted, and the predicted braking angle was compared with the detected-object angle for a safety evaluation. The safety level defined in this study consists of the three levels safe, warning, and emergency braking. The analytical rotational-inertia-based performance evaluation of the designed estimation algorithm was conducted using a typical working scenario. The results of the safety evaluation show that the predictive safety-evaluation algorithm of the proposed model can evaluate the safety level of the excavator during its operation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.12-24
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• 1997

An intelligent steering control system is designed for the steering control of a 4 wheel drive (4WD) electric vehicles without steering mechanism, where the vehicle is assumed to have 3 degree of freedom and input-output feedback linearization is employed. Especially, a fuzzy-rule-based side force estimator is suggested to avoid uncertain highlynonlinearexpression sof relations between side forces and their factors. Also, aneural-network-based predictive compensator is additionally utilized for the vehicle model to be correctly controlled with unstructured uncertainties. The proposed overall control system is numerically shown to be robust against drastic change of the external environments.