• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1113-1115
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• 1996

The servo system requires faster and more accurate dynamic responses. A new technique for the position control of DC servo motors is presented in this paper. The proposed technique employs a Self Tuning Regulator Proportional Integral Derivative(STR PID) position control systems in order to improve the dynamic performance of a DC servo motor. Recursive -least -squares (RLS) method is used in order to estimate the STR PID coefficients, $K_P$, $K_I$, and $K_D$. In order to consider dynamics such as voltage, angular velocity, and rotor angle, the above method was applied position control system.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.28-35
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• 2010

This paper presents new Adaptive Linear Combination Structure (ADALINE) for tracking/estimating voltage-current phasor and frequency of power system. To estimate the phasors and frequency from sampled data, the algorithm assumes that orthogonal coefficients and speed of angular frequency of power system are unknown parameters. With adequate sampled data, the estimation problem can be considered as a linear weighted least squares (LMS) problem. In addition to determining the phasors (orthogonal coefficients), the procedure estimates the power system frequency. The main algorithm is verified through a computer simulation and data from field. The proposed algorithm is tested with transient and dynamic behaviors during power swing, a step change of frequency upon islanding of small generators and disconnection of load. The algorithm shows a very high accuracy, robustness, fast response time and adaptive performance over a wide range of frequency, from 10 to 2000 Hz.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.153-158
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• 2008

This paper deals with the geometric fitting algorithms for parametric curves and surfaces in 2-D/3-D space, which estimate the curve/surface parameters by minimizing the square sum of the shortest distances between the curve/surface and the given points. We identify three algorithmic approaches for solving the nonlinear problem of geometric fitting. As their general implementation we describe a new algorithm for geometric fitting of parametric curves and surfaces. The curve/surface parameters are estimated in terms of form, position, and rotation parameters. We test and evaluate the performances of the algorithms with fitting examples.

• Nuclear Engineering and Technology
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• v.32 no.5
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• pp.485-494
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• 2000

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique . Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors.

• Journal of Power System Engineering
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• v.6 no.1
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.627-641
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• 2021

An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.380-381
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• 2019

This paper presents a grid voltage-sensorless current control design for an LCL-filtered grid-connected inverter with the purpose of enhancing the reliability and reducing the total cost of system. A disturbance observer based on the gradient steepest descent method is adopted to estimate the grid voltages with high accuracy and light computational burden even under distorted grid conditions. The grid fundamental components are effectively extracted from the estimated gird voltages by means of a least-squares algorithm to facilitate the synchronization process without using the conventional phase-locked loop. Finally, the estimated states of inverter system obtained by a discrete current-type full state observer are utilized in the state feedback current controller to realize a stable voltage-sensorless current control scheme. The effectiveness of the proposed scheme is validated through the simulation results.

• Journal of Korea Trade
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• v.24 no.5
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• pp.1-17
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• 2020

Purpose - This paper tries to estimate the effects of China's and Japan's free trade agreement (FTA) by panel generalized least squares (GLS). Design/methodology - The GLS model includes the basic gravity theory and Difference in Difference (DD) method to divide FTA conclusion countries and non-FTA conclusion countries with China and Japan. In order to empirically research the difference between Chinese and Japanese FTAs, we use the Difference in Difference in Difference (DDD) method. Findings - This paper finds the distance variable has more influence on Japanese than Chinese trade. The exchange rate indicates that Chinese trade depends on export and Japanese trade has the structure of re-import; shows that the countries that concluded FTAs with China and Japan have more positive trade effects than those that did not; finds the Chinese FTA promotion effects greater than the Japanese FTA because China had pushed ahead with trade policy since joining the WTO in 2001. Originality/value - This study shows that a single country's FTA and trade policies are an important factor concerning not just the promotion of trade but also the issue of trade conflicts.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.157-177
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• 2022

In this paper, an innovative finite element updating method is presented based on the variation wavelet transform coefficients of Auto/cross-correlations function (WTCF). The Quasi-linear sensitivity of the wavelet coefficients of the WTCF concerning the structural parameters is evaluated based on incomplete measured structural responses. The proposed algorithm is used to estimate the structural parameters of truss and plate models. By the solution of the sensitivity equation through the least-squares method, the finite element model of the structure is updated for estimation of the location and severity of structural damages simultaneously. Several damage scenarios have been considered for the studied structure. The parameter estimation results prove the high accuracy of the method considering measurement and mass modeling errors.

• Analytical Science and Technology
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• v.37 no.1
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• pp.12-24
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• 2024

In this study, laser-induced breakdown spectroscopy (LIBS) was used to estimate the degree of rice polishing. As-threshed rice seeds were dehusked and polished for different times, and the resulting grains were analyzed using LIBS. Various atomic, ionic, and molecular emissions were identified in the LIBS spectra. Their correlation with the amount of polished-off matter was investigated. Na I and Rb I emission line intensities showed linear sensitivity in the widest range of polished-off-matter amount. Thus, univariate models based on those lines were developed to predict the weight percent of polished-off matter and showed 3-5 % accuracy performances. Partial least squares-regression (PLS-R) was also applied to develop a multivariate model using Si I, Mg I, Ca I, Na I, K I, and Rb I emission lines. It outperformed the univariate models in prediction accuracy (2 %). Our results suggest that LIBS can be a reliable tool for authenticating the degree of rice polishing, which is closed related to nutrition, shelf life, appearance, and commercial value of rice products.