• 대한수학회지
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• 제48권4호
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• pp.775-795
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• 2011

The disturbance attenuation problem for a class of discretetime switched linear systems with exponential uncertainties via switched state feedback and switched dynamic output feedback is investigated, respectively. By using Taylor series approximation and convex polytope technique, exponentially uncertain discrete-time switched linear system is transformed into an equivalent switched polytopic model with additive norm bounded uncertainty. For such equivalent switched model, one designs its switching strategy and associated state feedback controllers and dynamic output feedback controllers so that whole switched model is asymptotical stabilization with H-in nity disturbance attenuation base on switched Lyapunov function and LMI approach. Finally, two numerical examples are presented to illustrate our results.

• 로봇학회논문지
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• 제5권2호
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• pp.160-168
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• 2010

In order to achieve a force controller with high performance, an accurate torque servo is required. However, the precise torque servo for a double vane rotary actuator system has not been developed till now, due to many nonlinear characteristics and system parameter variations. In this paper, the torque servo structure for the double vane rotary actuator system is proposed based on the torque model. Nonlinear equations are set up using dynamics of the double vane rotary hydraulic actuator system. Then, to derive the torque model, the nonlinear equations are linearized using a taylor series expansion. Both effectiveness and performance of the design of torque servo are verified by torque servo experiments and applying the suggested torque model to an impedance controller.

• 응용통계연구
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• 제28권6호
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• pp.1235-1243
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• 2015

최근 들어 ICT 분야의 발달에 따라 데이터 사용량의 급격한 증가로 인터넷 트래픽 사용량 예측은 중요성은 강조되고 있다. 이러한 예측치를 적절한 트래픽 관리와 제어를 위한 계획 수립에 도움을 준다. 본 논문은, 5분 단위의 인터넷 트래픽 자료를 이용하여 결합 예측 모형을 제안하고자 한다. 이에 대하여 시계열의 대표적인 3개 모형인 Seasonal ARIMA, Fractional ARIMA(FARIMA), Taylor의 수정된 Holt-Winters 모형을 적용하였다. 모형 간 결합 예측 방법으로 예측치 간의 SA(Simple Average) 결합 예측 방법과 OLS(Ordinary Least Square)를 이용한 결합방법, ERLS(Equality Restricted Least Squares)를 이용한 결합 예측 방법, Armstrong(2001)이 제안한 MSE 기반 결합 예측 방법을 사용한다. 이에 따른 결과로서 3시간에서의 예측은 Seasonal ARIMA가 선택된 반면, 6시간 이후 예측에서는 결합 예측 방법이 좋은 예측 성능을 보여준다.

• 비파괴검사학회지
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• 제36권2호
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• pp.93-101
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• 2016

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.

• JSTS:Journal of Semiconductor Technology and Science
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• 제12권4호
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• pp.473-481
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• 2012

For a mesa-isolated small geometry SOI MOSFET, the potentials in the silicon film, front, back, and side-wall oxide layers can be derived three-dimensionally. Using Taylor's series expansions of the trigonometric functions, the derived potentials are written in terms of the natural length that can be determined by using the derived formula. From the derived 3-D potentials, the minimum values of the front and the back surface potentials are derived and used to obtain the closed-form expressions for the front and back gate threshold voltages as functions of various device parameters and applied bias voltages. Obtained results can be found to explain the drain-induced threshold voltage roll-off and the narrow width effect of a fully depleted small geometry SOI MOSFET in a unified manner.

• 한국정밀공학회지
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• 제21권1호
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• pp.173-180
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• 2004

This paper presents the effect of varying boundary conditions such as ground subsidence, internal pressure and temperature variation for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function incorporating with von-Mises failure criteria is used in order to estimate the probability of failure mainly associated with three cases of ground subsidence. Using stresses on the buried pipelines, we estimate the probability of pipelines with von-Mises failure criterion. The effects of varying random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the pipeline crossing ground subsidence regions which have different soil properties.

• Smart Structures and Systems
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• 제6권2호
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• pp.101-113
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• 2010

This paper presents the results of a series of experiments conducted to model a magnetorheological damper operated in shear mode. The prototype MR damper consists of two parallel steel plates; a paddle covered with an MR fluid coated foam is placed between the plates. The force is generated when the paddle is in motion and the MR fluid is reached by the magnetic field of the coil in one end of the device. Two approaches were considered in this experiment: a parametric approach based on the Bingham, Bouc-Wen and Hyperbolic Tangent models and a non parametric approach based on a Neural Network model. The accuracy to reproduce the MR damper behavior is compared as well as some aspects related to performance are discussed.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제50권3호
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• pp.115-119
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• 2001

This paper presents an efficient and simple method for analyzine maximum simultaneous switching noise (SSN) on ground interconnection networks in CMOS systems. For the derivation of maximum SSN expression, we use ${\alpha}$-power law MOS model and Taylor's series approximation. The accuracy of the proposed method is verified by comparing the results with those of previous researches and HSPICE simulations under the contemporary process parameters and environmental conditions. The proposed method predicts the maximum SSN values more accurately when compared to existing approaches even in most practical cases such that exist some output drivers not in transition.

• 한국막학회:학술대회논문집
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• 한국막학회 1998년도 춘계 총회 및 학술발표회
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• pp.105-109
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• 1998

1. Introduction : In microfiltration the transport, deposition and removal of particles control cake formation on a filter. In this connection a new model on cake formation, based on the wall shear stress, was tested here in comparison with experiments of fine particle slurry under Taylor-vortex flow. The model expresses the deposition process for particles as two first-order steps in series of mass transfer and adhesion, and their removal process as a linear relation to the wall shear stress. This embraces characteristics of both dead-end and crossflow filtration. The correlation resulting from fitting to experimental data represented the experimental data reasonably well. This study will be helpful in analyzing fouling in heat exchangers.

• 말소리와 음성과학
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• 제6권2호
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• pp.29-34
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• 2014

In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.