• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1062-1070
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• 2018

This paper presents a simple identification method for discrete-time low-order model of unknown delay process from pulse response. The key idea is to find the parameters of the model such that the first N moments of the unknown process and the model are equal. We first show that the k-th moment of a process can be determined by the moments of the input and output. The parameters and delay are estimated separately. It is shown that for a given delay, the parameters of the low-order model can be determined by solving linear equations in a matrix form. Delay of the model is estimated such that the integral of the absolute errors (IAE) of the candidate models with possible delays minimizes. The illustrative example shows that the proposed method can directly identify low-order models without order reduction process from a single pulse response.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1535-1544
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• 2017

Advances in FPGA technology have enabled fast real-time simulation of power converters, filters and loads. FPGA based HIL (Hardware-In-the-Loop) simulators have revolutionized control hardware and software development for power electronics. Common time step sizes in the order of 100ns are sufficient for simulating switching frequency current and voltage ripples. In order to keep the time step as small as possible, ideal switching function models are often used to simulate the phase legs. This often produces inferior results when simulating the discontinuous conduction mode (DCM) and disabled operational states. Therefore, the corresponding measurement and protection units cannot be tested properly. This paper describes a new solution for this problem utilizing a discrete-time PI controller. The PI controller simulates the proper DC and low frequency AC components of the phase leg voltage during disabled operation. It also retains the advantage of fast real-time execution of switch-based models when an accurate simulation of high frequency junction capacitor oscillations is not necessary.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2712-2723
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• 1994

Numerical simulation of an axisymmetric ethylene-air jet diffusion flame has been carried out in order to investigate flame dynamics and soot formation. The model solves the time-dependent Navier-Stokes equations and includes models for soot formation, chemical reaction, molecular diffusion, thermal conduction, and radiation. Numerically FCT(Flux Corrected Transport) and DOM(Discrete Ordinate Method) methos are used for convection and radiation trasport respectively. Simulation was conducted for a 5 cm/sec fuel jet flowing into a coflowing air stream. The maximum flame temperature was found to be approximately 2100 K, and was located at an axial position of approximately 5 cm from the base of the flame. The maximum soot volume fraction was about $7{\times}10^{-7}$, and was located within the high temperature region where the fuel mole fraction ranges from 0.01 to 0.1. The buoyancy-driven low-frequency(12~13 Hz) structures convected along the outer region of the flame were captured. In case without radiation trasport, the maximum temperature was higher by 150 K than in case with radiation. Also the maximum soot volume fraction reached about $8{\times}10^{-6}$. As the the hydrocarbon fuel forms many soot particles, the radiation transport becomes to play a more important role.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.785-791
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• 2011

Two-lane and two-way traffic flow shows various dynamic relationships according to the behaviors of low-speed vehicle and overtaking. And it is essential to develop a vehicle model which simultaneously explains the behaviors of low-speed vehicle and overtaking using opposite lane in order to microscopically analyze various two-lane and two-way traffic flows by traffic flow simulation. In Korea, some studies for car-following and lane-changing models for freeway or signalized road have been reported, but few researches for the development of vehicle model for two-lane and two-way highway have been done. Hence, a microscopic two-lane and two-way vehicle model was, in this study, developed with the consideration of overtaking process and is based on CA (Cellular Automata) which is one of discrete time-space models. The developed model is parallel combined with an adjusted CA car-following model and an overtaking model. The results of experimental simulation showed that the car-following model explained the various macroscopic relationships of traffic flow and overtaking model reasonably generated the various behaviors of macroscopic traffic flows under the conditions of both opposite traffic flow and stochastic parameter to consider overtaking. The vehicle model presented in this study is expected to be used for the simulation of more various two-lane, two-way traffic flows.