• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.1
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• pp.58-67
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• 1987

By use of the real recorded data obtained from a power plant, nonlinear low-order state space models are developed for an once-through type power plant boiler. In order to understand the boiler dynamics and to use for the back-up controller design, the unknown model parameters have been estimated using the nonlinear estimation technique, i.e. Extended Kalman Filter method. It is shown that the simulation results coincide with the measurement data within 5% relative error range, which are acceptable from a back-up controller design point of view.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.20-30
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• 2001

In the paper, we propose a predictive control scheme using multiple neural network-based prediction models. To construct the multiple models, we select several specific values of a parameter whose variation affects serious control performance in the plant. Among the multiple prediction models, we choose one that shows the best predictions for future outputs of the plant by a switching technique. Based on a nonlinear programming method, we calculate the current process input in the nonlinear predictive control system with multiple prediction models. The proposed control method is shown to be very effective when a parameter of the plant changes or the time delay, if it exists, varies. It is also shown that the proposed method is successfully applied for the control of suspension in a electro-magnetic levitation system.

• Journal of the Korea Society for Simulation
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• v.4 no.1
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• pp.121-130
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• 1995

This paper deals with modeling and simulation of an industrial benzene-toluene-xylene plant. Because the fractionation unit of benzene-toluene-xylene plant has a narrow range of boiling point and doesn't have any sidecut and side reboiler, we employed boiling point estimation method in the modeling and simulation of the plant. Soave-Redlich-Kwong equation was used in the computation of thermodynamical properties. We solved resulting nonlinear equations by using Newton-Raphson method which is known to show fast convergence. Results of simulation showed good agreement with actual plant operation data.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.320-324
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• 2000

Nonlinear stress analysis of nuclear containment building is carried out using microscopic concrete material model. The present study mainly focuses on the evaluation of the ultimate pressure capacity of idealized containment building in nuclear power plant. For this purpose, an eight-node degenerated shell element it adopted and an imaginary opening in the apex of containment building is allowed in FE model. From numerical analysis, the adopted concrete material model performs well and has a good agreement with the result obtained by using ABAQUS. Finally, we propose the present study as a benchmark test for nonlinear analysis of containment building.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.284-284
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• 2000

In adaptive fuzzy control systems. fuzzy systems are used to approximate the unknown plant nonlinearities. Until now. most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure based on system state availability. This paper considers observer-based nonlinear controller and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters for state observer and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.236-236
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• 2000

Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.127-131
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• 1993

A new learning method of both NNI and NNC by which the NNI identifies precisely the dynamic characteristics of the plant is proposed. For control of ihe nonlinear plant we use two neural networks, one -for identification and the other for control. We define a closed loop en-or which depends on identification and control error. In the proposed learning method, the closed loop en-or is utilized to train the NNI and the NNC. Computer simulation results reveal that the NNC based on proposed method is insensitive to variations of the plant parameters.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.148-151
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• 2004

The hardening of concrete after setting is accompanied with nonlinear temperature distribution caused by development of hydration heat of cement. Especially at early ages, this nonlinear distribution has a large influence on the tensile cracking. As a result, in order to predict the exact temperature distribution in concrete structures it is required to examine thermal properties of concrete. In this study, the coefficient of air convection for concrete mix of nuclear power plant, which presents thermal transfer between surface of concrete and air, was experimentally investigated with variables such as velocity of wind and types of form. The coefficient of air convection obtained from experiment increases with velocity of wind, and its dependance on wind velocity is varied with types of form. This tendency is due to a combined heat transfer system of conduction through form and convection to air. The coefficient of air convection for concrete mix of nuclear power plant obtained from this study was well agreed with the existing models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1063-1066
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• 1995

This paper presents a precition control of an electrostatic microactuator. For the generation of sufficient electrostatic force, a donse comb-type electrostatic microactuator is designed and manufactureed via MEMS (micro-electro-mechanical systems) process. The nonlinear plant and the linear plant of the microactuator are established through the comparison of experimental results and simulation results. A feedforward controller is designed via MATLAB simulation using the inverse function of the nonlinear plant. the experiment for the precise position tracking control is undertaken to show the control efficiency of the proposed controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.604-611
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• 2013

This paper presents an second harmonic elimination method based on the impedance variation scheme. Through the power quality analysis from the nonlinear loads connected on the power system, the second harmonic problems have been analyzed with a case study analysis and the experiments. In the paper, the second Harmonic generation was simulated with a single phase SCR rectifier and the analytical model is proposed for the second harmonic generation. A novel impedance variation scheme is proposed and analyzed to eliminate the second harmonic. The experiment has been performed on the 60(MVA) industry manufacturing plant. The experimental result demonstrates the proposed impedance variation scheme successfully operate on the 60(MVA) industry manufacturing plant.