• Journal of the Korean Solar Energy Society
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• v.32 no.spc3
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• pp.235-244
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• 2012

This paper presents a design and simulation of bi-directional DC/DC boost converter for a fuel cell system. In this paper, we analyze the equivalent model of both a boost converter and a buck converter. Also we propose the controller of bi-directional DC-DC converter, which has buck mode of charging a capacitor and boost mode of discharging a capacitor. In order to design a controller, we draw bode plots of the control-to-output transfer function using specific parameters and incorporate proper compensator in a closed loop. As a result, it has increased PM(Phase Margin) for better dynamic performance. The proposed bi-directional DC-DC converter's 3pole-2zero compensation method has been verified with computer simulation and simulation results obtained demonstrates the validity of the proposed control scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.491-499
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• 2001

In this paper, the scheme of an efficient fuzzy rule generation and fuzzy system construction using GA(genetic algorithm) and FCM(fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. In the structure identification, input data is transformed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, a set fuzzy rules are generated for a given criterion by FCM clustering algorithm . In the parameter identification premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this one can systematically obtain the valid number of fuzzy rules which shows satisfying performance for the given problem. Finally, we applied the proposed method to the Box-Jenkins data and rice taste data modeling problems and obtained a better performance than previous works.

• Geophysics and Geophysical Exploration
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• v.2 no.1
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• pp.43-53
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• 1999

Numerical modeling and inversion for electromagnetic exploration methods are essential to understand behaviour of electromagnetic fields in complex subsurface. In this study, a finite element method was adopted as a numerical scheme for the 2.5-dimensional forward problem. And a finite element equation considering linear conductivity variation was proposed, when 2.5-dimensional differential equation to couple eletric and magnetic field was implemented. Model parameters were investigated for near-field with large source effects and far-field with responses dominantly by homogeneous half-space. Numerical responses by this study were compared with analytic solutions in homogeneous half-space. Blocky inversion model was modified to be applied to the forward calculation in this study and it was also adopted in the inversion algorithm. Resolution for isolated bodies were investigated to confirm possibility and limitation of inversion for electromagnetic exploration data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.197-201
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• 2007

Vibration characteristics of an annular cylindrical fuel rod, which was proposed as a candidate design of fuel's cross section for the ultra-high burnup nuclear fuel, according to the cross-sectional dimensions and the number of supports or the span length were analytically studied. Finite element(FE) modeling for the annular cross sectional fuel was based on the methodology, that have been proven by the test verification, for the conventional PWR nuclear fuel rod. A commercial FEA code, ABAQUS, was used for the FE modeling and analysis. A planar beam element (B21) that uses a linear interpolation was used for the fuel rod and a linear spring element for the spring and dimple of the SG. Natural frequencies and mode shape were calculated according to the preliminary design candidates for the fuel's cross sectional dimension and the number of span. From the analysis results, the design scheme of the annular fuel compatible to the present PWR nuclear reactor core was discussed in terms of the number of supports and fuel's cross section.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.32-42
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• 2000

This paper presents an on-line learning algorithm for sequential construction of generalized radial basis function networks (GRBFNs) to model nonlinear systems from empirical data. The GRBFN, an extended from of standard radial basis function (RBF) networks with constant weights, is an architecture capable of representing nonlinear systems by smoothly integrating local linear models. The proposed learning algorithm has a two-stage learning scheme that performs both structure learning and parameter learning. The structure learning stage constructs the GRBFN model using two construction criteria, based on both training error criterion and Mahalanobis distance criterion, to assign new hidden units and the linear local models for given empirical training data. In the parameter learning stage the network parameters are updated using the gradient descent rule. To evaluate the modeling performance of the proposed algorithm, simulations and their results applied to two well-known benchmarks are discussed.

• Structural Engineering and Mechanics
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• v.18 no.5
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• pp.645-669
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• 2004

In seismic analysis of moment-resisting frames, beam-column connections are often modeled with rigid joint zones. However, it has been demonstrated that, in ductile reinforced concrete (RC) moment-resisting frames designed based on current codes (to say nothing of older non-ductile frames), the joint zones are in fact not rigid, but rather undergo significant shear deformations that contribute greatly to global drift. Therefore, the "rigid joint" assumption may result in misinterpretation of the global performance characteristics of frames and could consequently lead to miscalculation of strength and ductility demands on constituent frame members. The primary objective of this paper is to propose a rational method for estimating the hysteretic joint shear behavior of RC connections and for incorporating this behavior into frame analysis. The authors tested four RC edge beam-column-slab connection subassemblies subjected to earthquake-type lateral loading; hysteretic joint shear behavior is investigated based on these tests and other laboratory tests reported in the literature. An analytical scheme employing the modified compression field theory (MCFT) is developed to approximate joint shear stress vs. joint shear strain response. A connection model capable of explicitly considering hysteretic joint shear behavior is then formulated for nonlinear structural analysis. In the model, a joint is represented by rigid elements located along the joint edges and nonlinear rotational springs embedded in one of the four hinges linking adjacent rigid elements. The connection model is able to well represent the experimental hysteretic joint shear behavior and overall load-displacement response of connection subassemblies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1128-1140
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• 2009

In this paper, we present a patient real-time vital sign information transmission system to effectively support developing real-time communication service by using a real-time object model named TMO (Time-Triggered Message-Triggered Object). Also, we describe the application environment as the ICU(Intensive Care Unit) to guarantee real-time service message with TMO structure in distributed network systems. We have to design to obtain useful vital sign information, which is generated at parsing data receiver modulor of HIS with TMO structure, that is offered by the central monitor. Vital sign informations of central monitor is composed of the raw data of several bedsite patient monitors. We are willing to maintain vital sign information of real time and continuity that is generated from the bedsite patient monitor. It is able to apply to remote medical examination and treatment. we proposed integration method between a vital sign database systems and hospital information systems. In the real time simulation techniques based on TMO object modeling, We have observed several advantages to the TMO structuring scheme. TMO object modeling has a strong traceability between requirement specification and design.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.627-633
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• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.183-191
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• 2006

The accuracy of the upward continuation is assessed through the gravity modeling using an ultra-high degree spherical harmonic expansion. The difficulties in the numerical calculation of Legendre function with ultra-high degree, underflow and/or overflow, is successfully resolved in 128 bit calculation scheme. Using the generated Legendre function, the gravity anomaly with spatial resolution of $1'{\times}1'$ on the geoid is calculated. The generated gravity anomaly is degraded and extracted with various noise levels and data intervals, then upward continuation is applied to each data sets. The comparison between the upward continued gravity disturbances and the directly calculated from the spherical harmonics showed that the accuracy on the direct method was significantly better than that of Poisson method. In addition, it is verified that the denser and less noised gravity data on the geoid generates better gravity disturbance vectors at an altitude. Especially, it is found that the gravity noise level less than 5mGal, and the data interval less than 2arcmin is necessary for next generation precision INS navigation which requires the accuracy of 5mGal or better at an altitude.