• 전자공학회논문지B
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• 제29B권2호
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• pp.18-26
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• 1992

MR(Model Reduction) is presented in order to estimate the frequency of multiple sinusoids from the finite noisy data with the white or colored noises. MR, using the reduced rank models, is designed, appling the approximation of linear system to LP(Linear Prediction). The MR method is analyzed. Monte-carlo simulations are conducted for MR and Lp. The results are compared with in terms of mean, root-mean square and relative bias. MR eliminates effectevely the extremeous and exceptional poles appearing in LP and improves the accuracy of LP. Especially, MR gives promising results in short noisy measurements, low SNR's and colored noises. Power spectral density and angular frequency position are showed by figures, for examples. Finally, the new method is utilized to the communication and biomedical systems estimating the characteristics of the signal and the system identification modelling the dynamic systems from experimental data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.229-231
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• 2006

The paper presents a sensorless speed control of interior permanent magnet synchronous motors using an adaptive integral binary observer in view of composition with a main loop regulator and an auxiliary loop regulator. The binary observer has a property of the chattering alleviation in the constant boundary layer; however, the steady state estimation accuracy and robustness are dependent upon with width of the constant boundary. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamic to the switching hyperplane equation.

• 경영과학
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• 제15권2호
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.

• ETRI Journal
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• 제31권4호
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• pp.393-398
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• 2009

The operation of a first-order 2-bit adaptive sigma-delta modulation system is described and discussed in this paper. The system operation is based on the combination of both "memory" and "look-ahead" estimation in the employed step-size adaptation algorithm of the basic quantizer. In comparison to simple systems and other adaptive sigma-delta systems, computer simulation results show that these features of the described system are responsible for the high SNR values and the extended dynamic range achieved for AC signals as well as the noise power reduction of almost 10 dB and the complete elimination of the idle tones for DC signals. However, such an advantageous performance requires the least possible multiplicative error accumulation, and this cannot be achieved without analog circuits of the highest possible accuracy.

• 대한기계학회논문집A
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• 제24권5호
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• pp.1133-1145
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• 2000

It is necessary to develop an efficient analysis method to identify the dynamic characteristics of a large mechanical structure and update its finite element model. That is because these processes need the huge computation of a large structure and iterative estimation due to the use of the first- order sensitivity. To efficiently carry out these processes, a new method, called the generalized free-interface mode sensitivity method, has been proposed in the authors' preceeding paper. This method is based on substructuring approach such as a free-interface method and a generalized synthesis algorithm. In this paper, the proposed method is applied to the model updating of a car body structure to verify its accuracy and reliability for a large mechanical structure.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2002년도 춘계학술대회
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• pp.9-15
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• 2002

This paper presents the seasonal forecasting of the occurrence of tropical cyclone (TC) over Western North Pacific (WNP) using the generalized linear model (GLM) and dynamic linear model (DLM) based on 51-year-data (1951-2001) in TC season (June to November). The numbers of TC and TY are predictands and 16 indices (the E1 Nino/Southern Oscillation, the synoptic factors over East asia and WNP) are considered as potential predictors. With 30-year moving windowing, the estimation and prediction of TC and TY are performed using GLM. If GLM forecasts have some systematic error like a bias, DLM is applied to remove the systematic error in order to improve the accuracy of prediction.

• 한국자동차공학회논문집
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• 제4권4호
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.175-177
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• 2001

Frequency and phasor are the most important quantities in power system operation. Frequency reflects the dynamic energy balance between load and generating power. To estimate of power system frequency, an accurate digital tracking algorithm by using phasor angle difference is presented. For an evaluation of the proposed technique, simulations by EMTP have been performed. Test results were showed the algorithm's accuracy under the effect of noise and changes in frequency and amplitude on the input signal.

• 전기의세계
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• 제20권3호
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• pp.8-16
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• 1971

The proper design of man-machine systems requires as much understanding of the human element as of the machine. Although the modern systems engineer can obtain a very high degree of repeatability and accuracy for the characteristics of a machine, these of the human elements are much less well known. Due to the complexity and importance of modern man-machine systems, this difficult problem has recently received increasing attention. In this paper, the dynamic characteristics of the human operator have been newly determined by impulse estimation using Pseuo-random binnary signals as a test signal and the quasi-linear human operator models used as an element of a closed-loop control system adopted from McRuer & Krendel and Bekey. Also the techniques and instruments are presented for correlating the actual characteristics of the constructed system with anticipated theoretical values. Consequently, in spite of many problems remain yet, experimental results were very satisfactory.

• Advances in robotics research
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• 제2권1호
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.