• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1645-1650
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• 2005

FOPDT(First-Order Plus Dead-Time) and SOPDT(Second-Order Plus Dead-Time) process, which are used as the most useful process in industry, are difficult about process identification because of the long dead-time problem and the model mismatch problem. Thus, the accuracy of process identification is the most important problem in FOPDT and SOPDT process control. In this paper, we proposed the real-coded genetic algorithm for identification of FOPDT and SOPDT processes. The proposed method using real-coding genetic algorithm shows better performance characteristic comparing with the existing an area-based identification method and a directed identification method that use step-test responses. The proposed strategy obtained useful result through a number of simulation examples.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2004년도 춘계학술대회
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• pp.179-193
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• 2004

Introduction of domestic digital content identification system mean to building district identification by supplying international identification system and interoperability that reflect domestic special state than accept it as it is. This study presented an policy direction for the domestic digital content identification system by the results that analyzed of the identification systems that were commonly used internationally. An identification system is composed to a registration authority, registration agencies, registrants. There should be defined their roles and set up their cooperative system to be able to bring efficiency into more.

• Journal of Electrical Engineering and information Science
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• 제3권1호
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• pp.86-93
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• 1998

In this paper, we propose an effective on-line identification method for rotor resistance, which is useful in making speed control of induction motors without rotational transducers robust with respect to the variation in rotor resistance. Our identification method for rotor resistance is based on the linearly perturbed equations of the closed-loop system for sensorless speed control about th operating point. Our identification method for rotor resistance uses only the information of stator currents and voltages. In can provide fairly good identification accuracy regardless of load conditions. Some experimental results are presented to demonstrate the practical use of our identification method. For our experimental work, we have built a sensorless control system, in which all algorithms are implemented on a DSP. Our experimental results confirm that our on-line identification method allows for high precision speed control of commercially available induction motors without rotational transducers.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.180-182
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• 2005

Fingerprint-based identification is known to be used for a very long time. Owing to their uniqueness and immutability, fingerprints are today the most widely used biometric features. Therefore, recognition using fingerprints is one of the safest methods as a way of personal identification. But fingerprint identification system has a critical weakness. Since the fingerprint identification time dramatically increase when we compare the unknown fingerprint's minutiae with fingerprint database's minutiae. In this paper, a ridge orientation extraction method using Index table is proposed to solve the problem. The goal of fast direction image extraction is to reduce the identification time and to improve the clarity of ridge and valley structures of input fingerprint image.

• Smart Structures and Systems
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• 제7권1호
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• pp.59-82
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• 2011

In this study, an output-only modal identification approach is proposed for decentralized wireless sensor nodes used for linear structural systems. The following approaches are implemented to achieve the objective. Firstly, an output-only modal identification method is selected for decentralized wireless sensor networks. Secondly, the effect of time-unsynchronization is assessed with respect to the accuracy of modal identification analysis. Time-unsynchronized signals are analytically examined to quantify uncertainties and their corresponding errors in modal identification results. Thirdly, a modified approach using complex mode shapes is proposed to reduce the unsynchronization-induced errors in modal identification. In the new way, complex mode shapes are extracted from unsynchronized signals to deal both with modal amplitudes and with phase angles. Finally, the feasibility of the proposed approach is evaluated from numerical and experimental tests by comparing with the performance of existing approach using real mode shapes.

• 대한전기학회논문지
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• 제45권4호
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• pp.574-581
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• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Networks(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Self-Organized Distributed Networks (SODN). The learning with the SODN is fast and precise. Such properties are caused from the local learning mechanism. Each local network learns only data in a subregion. This paper also discusses neural network as identifier of nonlinear dynamical systems. The structure of nonlinear system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems. (author). 13 refs., 7 figs., 2 tabs.

• 센서학회지
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• 제24권6호
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• pp.368-372
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• 2015

In this paper, we proposed a post-processing technique for improving classification performance of electronic nose (E-Nose) system which may be occurred drift signals from sensor array. An adaptive radial basis function network using stochastic gradient (SG) and singular value decomposition (SVD) is applied to process signals from sensor array. Due to drift from sensor's aging and poisoning problems, the final classification results may be showed bias and fluctuations. The predicted classification results with drift are quantized to determine which identification level each class is on. To mitigate sharp fluctuations moving-averaging (MA) technique is applied to quantized identification results. Finally, quantization and some edge correction process are used to decide levels of the fluctuation-smoothed identification results. The proposed technique has been indicated that E-Nose system was shown correct odor identification results even if drift occurred in sensor array. It has been confirmed throughout the experimental works. The enhancements have produced a very robust odor identification capability which can compensate for decision errors induced from drift effects with sensor array in electronic nose system.

• 한국운동역학회지
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• 제13권1호
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• pp.23-38
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• 2003

The purpose of this study is to develop an improved marker auto-identification algorithm for reduce of data processing time through improve the efficiency of noise elimination and marker separation. The maker auto-identification algorithm was programming named KUMAS used Delphi language. For the study, various experiments were conducted for the verification of KUMAS. and compared two systems of established with the KUMAS. Four different motions - cycling, gait, rotation, and pendulum -, were selected and tested. Motions were filmed 30Hz frames rate per second. ${\chi}^2$ used for statistical analysis. Significant level were ${\alpha}=.05$. The test results were as follow. 1. Increased the success ratio of marker auto-identification. 2. The efficiency of marker auto-identification was remarkably improved through marker separation, noise elimination. 3. The marker auto-identification ability was improved in 2D-image plane include the 3D motion. 4. Significant different were found between KUMAS and B-SYS(established system) with non-input the artificial noise frames, input the artificial noise frames and total frames.

• Journal of Power Electronics
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• 제17권6호
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• pp.1545-1552
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• 2017

Identifying the load and mutual inductance is essential for improving the power transfer capability and power transfer efficiency of Inductive Power Transfer (IPT) systems. In this paper, a steady-state load and mutual inductance identification method focusing on series-parallel compensated IPT systems is proposed. The identification model is established according to the steady-state characteristics of the system. Furthermore, two sets of identification results are obtained, and then they are analyzed in detail to eliminate the untrue one. In addition, the identification method can be achieved without extra circuits so that it does not increase the complexity of the system or the control difficulty. Finally, the feasibility of the proposed method has been verified by simulation and experimental results.

• Structural Engineering and Mechanics
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• 제78권3호
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• pp.369-378
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• 2021

This paper reviewed a few output-only system identification algorithms and identified the shortcomings of those popular blind source separation methods. To address the issues such as less sensors than the targeted modal modes (under-determinate problem), repeated natural frequencies as well as systems with complex mode shapes, this paper proposed a complex wavelet modified second order blind identification method (CWMSOBI) by transforming the time domain problem into time-frequency domain. The wavelet coefficients with different dominant frequencies can be used to address the under-determinate problem, while complex mode shapes are addressed by introducing the complex wavelet transformation. Numerical simulations with both high and low signal-to-noise ratios validate that CWMSOBI can overcome the above-mentioned issues while obtaining more accurate identified results than other blind identification methods.