• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.99-101
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• 2018

This paper present an input-series output-parallel active-clamp-forward converter for low voltage dc/dc xEV application. The converter can achieve ZVS turn-on for all switches. An accurate small signal model of the converter which includes the effect of leakage inductance is given and controller design based on modeling is described. Experimental and simulation results from a 3.2kW, 100kHz prototype are presented in order to verify the validity of the converter operation and the designed control parameters.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1196-1201
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• 2014

This paper presents an exploration on the effect of wind turbine contribution to the frequency control of individual systems that can be used for efficient power production in India. The research includes the study of Permanent Magnet Synchronous Generator (PMSG), in wind farms. The WTs are tested for inertia and for droop responses with intelligent fuzzy logic controllers (FLC) that choose Double Input Single Output (DISO) strategy that automatically sets gain constants, as well as combined responses for the WTs. Quantitative analyses are presented for the WTs for benefits and drawbacks including appropriate selection parameters. The analysis includes inertia, droop and combined inertia, droop schemes. The reconnaissance also incorporates inertia with FLC, droop with FLC, inertia and droop with FLC schemes for detailed study of WTs, so as to forecast and achieve proper frequency control. Moreover, the analysis provides the best suited method for frequency control in PMSG.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1551-1561
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• 2014

Design, Simulation and experimental analysis of closed loop time domain based Discrete PWM buck-boost converter are described. To improve the transient response and dynamic stability of the proposed converter, Discrete PID controller is the most preferable one. Discrete controller does not require any precise analytical model of the system to be controlled. The control system of the converter is designed using digital PWM technique. The proposed controller improves the dynamic performance of the buck-boost converter by achieving a robust output voltage against load disturbances, input voltage variations and changes in circuit components. The converter is designed through simulation using MATLAB/Simulink and performance parameters are also measured. The discrete controller is implemented, and design goal is achieved and the same is verified against theoretical calculation using LabVIEW.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.344-347
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• 2005

Helper T(Th) cells regulate immune response by producing various kinds of cytokines in response to antigen stimulation. The regulatory functions of Th cells are promoted by their differentiation into two distinct subsets, Th1 and Th2 cells. Th1 cells are involved in inducing cellular immune response by activating cytotoxic T cells. Th2 cells trigger B cells to produce antibodies, protective proteins used by the immune system to identify and neutralize foreign substances. Because cellular and humoral immune responses have quite different roles in protecting the host from foreign substances, Th cell differentiation is a crucial event in the immune response. The destiny of a naive Th cell is mainly controlled by cytokines such as IL-4, IL-12, and IFN-${\gamma}$. To understand the mechanism of Th cell differentiation, many mathematical models have been proposed. One of the most difficult problems in mathematical modeling is to find appropriate kinetic parameters needed to complete a model. However, it is relatively easy to get qualitative or linguistic knowledge of a model dynamics. To incorporate such knowledge into a model, we propose a novel approach, fuzzy continuous Petri nets extending traditional continuous Petri net by adding new types of places and transitions called fuzzy places and fuzzy transitions. This extension makes it possible to perform fuzzy inference with fuzzy places and fuzzy transitions acting as kinetic parameters and fuzzy inference systems between input and output places, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.213-218
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• 1991

A new model which contains the dynamics of the motor system and the kinematics of the timing belt system is derived for an inverted pendulum system in FAPA Lab. Generalized standard compensator configuration(SCC) which contains the variable design parameters Kl, K2, .., K5 is proposed so that any desired design specification can be achieved. The robust controller which has robust property against the influence of sensor noise, system parameter variation and model uncertainty is designed minimizing the H$_{\infty}$-norm of transfer function from exogenous input to controlled output. The method of solving the two Riccati equations in state space and determining the controller uses on iteration method where the unique stabilizing solution to two algebraic Riccati equation must be positive definite and the spectral radius of their product less than .gamma.$^{2}$. Some cases are derived by varying the design parameter for simulation on a digital computer and experimenting the H$_{\infty}$- controller on an analog computer. The design parameters of controller which satisfies the desired control specification is selected on the basis of the simulation result and experimenting. The reasonableness and validity of the simulation and the robustness of the controller is established.d.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.546-551
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• 2001

Space Test Department at KARI(Korea Aerospace Research Institute) plans to carry out the GVT(Ground Vibration Test) for the KSR(Korea Sounding Rocket)-III FM(Flight Model) which is being developed by Space Technology R＆D Division. KSR-III will be an intermediate to the launch vehicle capable of carrying satellites to their orbits. GVT offers very important information to predict the behavior of KSR in its operation, and to develop the flight control and aerodynamic analysis. For development of test facilities, testing and analysis methods which can be used for the future test, Space Test Department has performed the GVT with KSR-II PFM(Proto-Flight Model) at Satellite Integration ＆ Test Center of KARl This paper discusses the procedures, techniques and the results of it. In this test, to simulate free-free condition, test object hung in the air by 4 bungee cords specially devised. The GVT was carried out using pure random excitation technique with MIMO(Multi-Input-Multi-Output) method with three electromagnetic shakers, and poly-reference parameter estimation was used to identify the modal parameters. As the result of the test, 11 mode shapes and modal parameters below 200㎐ were identified and compared with analytical results.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.62.1-62.1
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• 2013

We present the Exposure Time Calculator of IGRINS (Immersion Grating Infrared Spectrograph). The noises of IGRINS and the simulated emission line can be calculated from the combination of Telluric background emission and absorptions, the emission and transmission of the telescope and instrument optics, and the dark noise and the read noise of the infrared arrays. For the atmospheric transmissions, we apply the simulated spectra depending on the Precipitable Water Vapor (PWV) values. In case of calculation of noises, the user needs to input the expected target magnitude, the weather conditions, and the desired exposure time. In addition to the simulated emission line, the parameters of rest wavelength, line-flux, Doppler shift and line-width are needed. The output would be the expected signal-to-noise for each spectral resolution element. The source-code of IGRINS-ETC v2.1.1 is available to be downloaded on the World Wide Web.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1815-1821
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• 2015

Rapid increase in population growth has made the mankind to delve in appropriate identification of individuals through biometrics. Foot Print Recognition System is a new challenging area involved in the Personal recognition that is easy to capture and distinctive. Foot Print has its own dimensions, different in many ways and can be distinguished from one another. The main objective is to provide a novel efficient automated system Segmentation using Foot Print based on structural relations among the features in order to overcome the existing manual method. This system comprises of various statistical computations of various foot print parameters for identifying the factors like Instep-Foot Index, Ball-Foot Index, Heel- Index, Toe- Index etc. The input is naked footprint and the output result to an efficient segmentation system thereby leading to time complexity.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.65-73
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• 2015

This paper presents a method of predicting the machining parameters on the turning process of low carbon steel using a neural network with back propagation (BP) and particle swarm optimization (PSO). Cutting speed, feed rate, and depth of cut are used as input variables, while surface roughness and electric current consumption are used as output variables. The data from experiments are used to train the neural network that uses BP and PSO to update the weights in the neural network. After training, the neural network model is run using test data, and the results using BP and PSO are compared with each other.