• Wind and Structures
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• v.20 no.1
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• pp.75-93
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• 2015

This work is focused on a parametric numerical study of the barrier's bar inclination shelter effect in crosswind scenario. The parametric study combines mesh morphing and design of experiments in automated manner. Radial Basis Functions (RBF) method is used for mesh morphing and Ansys Workbench is used as an automation platform. Wind barrier consists of five bars where each bar angle is parameterized. Design points are defined using the design of experiments (DOE) technique to accurately represent the entire design space. Three-dimensional RANS numerical simulation was utilized with commercial software Ansys Fluent 14.5. In addition to the numerical study, experimental measurement of the aerodynamic forces acting on a vehicle is performed in order to define the critical wind disturbance scenario. The wind barrier optimization method combines morphing, an advanced CFD solver, high performance computing, and process automaters. The goal is to present a parametric aerodynamic simulation methodology for the wind barrier shelter that integrates accuracy and an extended design space in an automated manner. In addition, goal driven optimization is conducted for the most influential parameters for the wind barrier shelter.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.25-34
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• 2000

In this paper, we design a H^\infty servo controller for gauge control of tandem cold mill. To improve the performance of the AGC(Aotomatic Gauge Control) system based on the Taylor linearized model of tandem cold mill, the H^\infty servo controller is designed to satisfy robust stability, disturbance attenuation and robust tracking properties. The H^\infty servo controller problem is modified as an usual H^\infty control problem, and the solvability condition of the H^\infty servo problem depends on the solvability of the modified H^\infty control problem. Since this modified problem does not satisfied standard assumptions for the H^\infty control problem, it is solved by an LMI(Linear Matrix Inequality) technique. Consequently, the comparison between the H^\infty servo controller and the existing PID/FF(FeedForward) controller shows the usefulness of this study.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.691-693
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• 2015

Radio sources are very weak, as they can travel through large distances. Radio sources also have photons with low energies compared to others electromagnetic waves (EM). Microwave photons have a little more energy than radio waves, infrared photons have still more, then visible, ultraviolet, X-rays, and the most energetic electromagnetic wave is gamma-rays. Radio astronomy studies are restricted due to radio frequency interference (RFI) produced by people. If this disturbance is not minimized, it poses critical problems for astrophysical studies. The purpose of this paper is to profile RFI maps in Peninsular Malaysia with a minimum mapping technique for RFI interference. Decision-making processes using GIS (Geographical Information System) for the selection requires gathering information for a variety of parameters. These factors affecting the selection process are also taken into account. In this study, various factors or parameters are involved, such as the availability of telecommunications transmission (including radio and television), rainfall, water lines and human activity. This mapping step must be followed by RFI site testing in order to identify areas of low RFI. This study will benefit radio astronomy research, especially regarding the RFI profile.

• Journal of Life Science
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• v.16 no.7 s.80
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• pp.1097-1103
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• 2006

Community structure varies not only in space but also in time. We stand in one position which located at Sinhung-ri, Sacheon-ci and observe the flora of area as time passes. This area begins after disturbance on sites where organisms are already present like secondary succession. In 2001, there are invaded by Trapa japonica, Salvinia natans, and Potamogon cristatus. Four or five years later, this abandoned areas support of clover, pine, and oak, resulting in a shifting pattern of species dominance and diversity through time. Patterns of community structure such as species composition and ecological diversity have shown through seasons and five years, that is the topic of this study. The values of turnover (TO) were changes through time intervals at three regions. The gradual and seemingly directional change in the structure of the community through time from aquatic like to field. Thus, we can observe the process of secondary succession at Sinhung-ri in the very short time.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1377-1379
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• 1996

In this paper, each parameter was identified by the gradient descent method to overcome difficulty deciding fuzzy rules of FLC for the unknown process and the type of membership Junctions. Usually PID or optimal control theories have been mostly usee in control field so far. However, optimal control requires much time for calculation because of adaptation for disturbance and nonlinearity. And intricate technique such as MRAS which can be realized only by an expert are limited to be used in the systems requiring rapid and precise response because of comparatively longer calculating time and complicateness. Gradient descent method is a method to find Z minimizing a function about a certain vector Z. And required output of FLC is gained using gradient approaching method in order to adapt control rule parameters of FLC. Simulation proved validation of this algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.315-320
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fired gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of Power Electronics
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• v.18 no.1
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.306-309
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• 2005

This parer describes the tracking control simulation of 6-DOF shaking table with a bell crank structure, which converts the direction of reciprocating movements. For the Joint coordinate-based control which uses lengths of each actuator, the trajectory conversion process inverse kinematics is performed. Applying the Newton-Euler approach, the dynamic equation of the shaking table is derived. To cope with nonlinear problems, time-delay control(TDC) is considered, which has been noted for its exceptional robustness to parameter uncertainties and disturbance, in addition to steady-state accuracy and computational efficiency. If the nominal model is equal to the real system, joint coordinate-based control can be very efficient. However, manufacturing tolerances installation errors and link offsets contaminate the nominal values of the kinematic parameters used in the kinematic model of the shaking table. To compensate differences between the nominal model and the real system. the joint coordinate-based control using acceleration feedback in the Cartesian coordinate space is proposed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.