• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.1
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• pp.9-19
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• 2016

Permanent deformation plays a key role in performance based earthquake resistant design. In order to estimate permanent deformation after earthquake, it is essential to secure reliable response history analysis(RHA) as well as earthquake scenario. This study focuses on permanent deformation of an inverted T-type wall under earthquake. The study is composed of two separate parts. The first one is on the verification of RHA and the second one is on an effect of input earthquake motion. The former is discussed in companion paper and the latter in this paper. In order to investigate the effect of an input earthquake motion on the permanent deformation, three bins of spectral matched real earthquake records with different magnitude, regions, epicentral distance are constructed. Parametric study was performed using the verified RHA through the companion paper for each earthquake records in the bins. The most influential parameter affecting permanent displacement is magnitude. The other parameters describing earthquake motion are not significant enough to increase permanent displacement of the inverted T-type wall except for energy related parameters(AI, CI, SEI).

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.335-338
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• 1998

This paper presents calculated results for the infinite phased arrays of the probe-fed rectagualr microstrip patches. A numerical model that is based on a rigorous Green's function and galerkin solutionsis is described. In an arbitrary scan plane, the input impedance and the input reflection coefficient versus the scand angle are calculated. The effects of substrate parameters on the phased arry antenna are considered. The scan blindness phenomenon due to the surface wave is observed and the input impedance bandwidth in the arbitrary scan plane is calculated.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1081-1084
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• 1991

A technique of indirect adaptive control based on certainty equivalence for input output linearization of nonlinear system is proven convergent by Teel. It incorporates an adaptive observer for identifying unknown system states and parameters and input-output linearizing controller for robust tracking. In this study, we show that robustness and tracking performances are improved considerably by using its normalized form of Teel's observer-based identifier. Simple examples are presented as illustration.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.509-512
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• 2012

This paper presents the state feedback control design for discrete time nonlinear systems where there exists a time delay in input. It is shown that under some boundedness condition, the time delay nonlinear systems can be transformed into the time delay linear systems with time varying parameters. Sufficient conditions for existence of stabilizing state feedback controller are characterized by linear matrix inequalities. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1667-1671
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• 2003

A computer program to calculate properties of nitrogen is developed. Procedures for the calculation is briefly discussed. The program calculates unknown thermodynamic properties fixing the state with two independent input properties. If input value by user is inappropriate, it displays an error message and replaces the input value with an appropriate one. In addition user can change units with easy. The program developed in this work can be utilized to calculate parameters required for the simulation and design of an equipment using nitrogen.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.168-173
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• 1987

The optimal Input design problem for linear system Which have the common parameters in the system and noise transfer functions. Exploiting the assumed Model structure and deriving the information matrix structure in detail, D-optimal open-loop stochastic input can be realized as an ARMA process under the Input or output variance constraints. In spite of the reduced order, It Is necessary to develop an efficient algorithms for the optimation with respect to the .rho..

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.153-156
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• 2001

This paper discusses a stochastic stabilization of Takagi-Sugeno (75) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time 75 fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized 75 fuzzy system is represented by a discrete-time 75 fuzzy system with jumping parameters. The stochastic stabilizibility of the jump 75 fuzzy system is derived and formulated in terms of linear matrix inequalities (LMls).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.507-512
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• 1987

Input/output equations in SDINS IMU are modeled from survey of IMU data flow. Given without precise equipments which can generate acceleration and angular velocity, a simple method is derived to calibrate the parameters of i/o eqijations. Also in order to upgrade ins performance, methods to estimate variant magnitudes of time variant parameters are surveyed.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.10-18
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• 2010

This paper presents a optimization of sigmoid activation function parameter using genetic algorithms and pattern recognition analysis in input space of two spirals benchmark problem. To experiment, cascade correlation learning algorithm is used. In the first experiment, normal sigmoid activation function is used to analyze the pattern classification in input space of the two spirals problem. In the second experiment, sigmoid activation functions using different fixed values of the parameters are composed of 8 pools. In the third experiment, displacement of the sigmoid function to determine the value of the three parameters is obtained using genetic algorithms. The parameter values applied to the sigmoid activation functions for candidate neurons are used. To evaluate the performance of these algorithms, each step of the training input pattern classification shows the shape of the two spirals.