• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.588-590
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• 1999

In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.341-345
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• 1997

A novel fuzzy basis function vector-based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the parameters of the compensator in the sense that both the asymptotic error convergence can be obtained for the colsed loop nonlinear control system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.713-723
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• 1995

In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the technology for adaptively optimizing the cutting conditions to maximize the material removal rate in face milling operations is proposed using the exterior penalty function method combined with multilayered neural networks. Two neural networks are introduced ; one for estimating tool were length, the other for mapping input and output relations from experimental data. Then, the optimization of cutting conditions is adaptively implemented using tool were information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine and finish cutting.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.22-25
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• 2002

The Mass production of ceramic heater has encountered with the estimation for the proper parameters of the printing conditions. This paper presents a method to estimate the squeegee pressure. It uses resistance distribution from the trial run with approximate squeegee pressure which comes from statistical process control (SPC). Then, the resistance distribution and its total resistance are input to the backpropagation neural networks that can recognize resistance's distribution patterns. The value of output network derived from the input value can identify to the appropriate squeegee pressure. The experimental results are demonstrated In ensure the efficiency and the reliability of this method with the accuracy 96.75 percent. Indeed, embedded on this method will aid us to reduce the loss from the normal mass production.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.337-346
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• 2004

The control scheme using fuzzy modeling and Parallel Distributed Compensation (PDC) concept is proposed to provide asymptotic tracking of a reference signal for the flexible joint manipulators with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop multi-input/multi-output system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Journal of the Korean Solar Energy Society
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• v.23 no.4
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• pp.11-20
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• 2003

This study aims to develop the program for active solar heating system design & analysis. The program, named ASOLis, is consisted of three user's interface like as system input/output, library, and utilities and used TRNSYS as a calculation engine for the system analysis. ASOLis simplifies user's input data through the database and can design 37 different types of solar systems. Solar system is configurated by two separated parts "solar thermal collecting part" and "load supplying part". Due to the user-friendly layout, all design parameters can be changed quickly and easily for the influence on system efficiency. For the reliability, ASOLis compared with experimental result. As a result, ASOLis is expected to be used as a vital tool for the design and analysis of active solar heating system.

• Journal of Magnetics
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• v.21 no.4
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• pp.491-495
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• 2016

We developed an embedded Object-Oriented Micromagnetic Frame (OOMMF) script schemes for more flexible simulations for complex and dynamic mircomagnetic behaviors. The OOMMF can be called from any kind of softwares by system calls, and we can interact with OOMMF by updating the input files for next step from the output files of the previous step of OOMMF. In our scheme, we set initial inputs for OOMMF simulation first, and run OOMMF for ${\Delta}t$ by system calls from any kind of control programs. After executing the OOMMF during ${\Delta}t$, we can obtain magnetization configuration file, and we adjust input parameters, and call OOMMF again for another ${\Delta}t$ running. We showed one example by using scripting embedded OOMMF scheme, tunneling magneto-resistance dependent switching time. We showed the simulation of tunneling magneto-resistance dependent switching process with non-uniform current density using the proposed framework as an example.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2002.02a
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• pp.109-110
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• 2002

The purpose of a superconductive DC/SFQ circuit is to produce a controlled number of picosecond single flux quantum pulses at the output when a slowly changing DC current is applied to the input. In this work, we have designed and simulated a DC/SFQ circuit based on Nb/Al$O_{x}$/Nb Josephson junction technology. From the simulation, we could obtain the margins for various circuit parameters. And also we have successfully operated a DC/SFQ circuit which was fabricated with the same design. The margin for the input bias current of the circuit was observed to be of $\pm$60%, which was very close to the simulated value.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.690-695
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• 2004

The present study is an investigation on the characteristics of heavy load toque converter by experimental process. To get the dynamic performance, the dynamometer was used with a parameters of speed, torque, oil pressure and oil flux, etc. The torque converter was tested for various input speed, output oil pressure and input oil flow rate. All experiments were investigated in case that the speed ratio is increased. The torque ratio and capacity factor was in inverse proportion to speed. Engine revolution had a more effects at region of low speed ratio. But, the opposite phenomena were represented increase of efficiency. In result of this experiments, the characteristics of torque converter were not influenced by oil pressure and oil flux.