• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1999년도 제29회 춘계학술대회
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• pp.175-181
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• 1999

The present work is an attempt to calculate the steady state pressure and perturbed pressure of journal bearings that has a helical groove. A coordinate is fitted to the helical groove and governing equation is derived by applying generalized coodinate system to the divergence formulation method. This method makes it possible to deal with an arbitrary configuration of a lubricated surface. The dynamical response of shaft-bearing system is calculated using the bearing reaction force and external force.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.8-17
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• 2015

This paper analyses the power flow of a three-feeder/multi-bus distribution system by a custom Generalized Power Quality Conditioner (GUPQC). The GUPQC has been realized by three voltage source converters (VSCs) coupled back-to-back through a common DC-link capacitor on the DC-side. One feeder was controlled by the shunt compensator, whereas each of the other two feeders was controlled by the proposed novel series compensator. The GUPQC has the capability to simultaneously compensate voltage and current quality problems of a multi-bus/three-feeder distribution system. Besides that, the power can be transferred from one feeder to other feeders to compensate for poor power quality problems. Extensive simulation studies were carried out by using MATLAB/SIMULINK software to establish the ability of the GUPQC to improve power quality of the distribution systems under distorted supply voltage conditions.

• 한국CDE학회논문집
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• 제10권4호
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• pp.284-292
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• 2005

This paper presents a new framework of kinematic tolerance synthesis and describes the implemented algorithm for planar mechanical systems comprised of higher kinematic pairs. Input to the synthesis algorithm is a parametric model of the mechanical system with allowed parameter ranges (tolerance ranges). The model is specified as the part profiles consisting of line and arc segments and the motion axes along which each part moves. The algorithm analyzes tolerance in generalized configuration space, called contact zones bounding the worst-case variations, and identifies bad system variations. The bad system variations then are removed out of the parameter ranges by adjusting the nominal parameter values if possible and then shrinking the ranges otherwise. This cycle is repeated until no more bad variations we found. I show the effectiveness of the algorithm by case studies on several mechanisms.

• Journal of Mechanical Science and Technology
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• 제16권10호
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• pp.1239-1245
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• 2002

A formulation which seeks steady-state equilibrium positions of constrained multibody systems driven by constant generalized speeds is presented in this paper. Since the relative coordinates are employed, constraint equations at cut joints are incorporated into the formulation. To obtain the steady-state equilibrium position of a multibody system, nonlinear equations are derived and solved iteratively. The nonlinear equations consist of the force equilibrium equations and the kinematic constraint equations. To verify the effectiveness of the proposed formulation, two numerical examples are solved and the results are compared with those of a commercial program.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.172.4-172
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• 2001

In this paper, the Generalized Predictive Control(GPC) method based on Fuzzy Neural Networks(FNNs) is presented for the control of chaotic nonlinear systems without precise mathematical models. In our method, FNNs is used as the predictor whose parameters are tuned by the error between the actual output of nonlinear chaotic system and that of FNNs model. The parameters of GPC controller are adjusted via the gradient descent method where the difference between the actual output and the reference signal is used as a control error. Finally, computer simulation on the representative continuous-time chaotic system(Duffing system) is presented to demonstrate the effectiveness of our chaos control method.

• 한국소음진동공학회논문집
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• 제13권10호
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• pp.813-820
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• 2003

Conventional modal analysis techniques are known to be inappropriate for asymmetrical rotor systems, when the equations of motion are written in the stationary coordinates, due to the presence of time varying parameters. This paper presents a generalized modal analysis method for asymmetrical rotor systems in the stationary coordinates, employing the modulated coordinates and the lambda matrix formulation. A numerical example with a flexible asymmetric rotor model is provided to demonstrate the effectiveness of the proposed modal analysis method. As an application of the proposed method, modal analysis is also performed with an open cracked rotor system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.176-181
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• 1992

In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

• 동력기계공학회지
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• 제9권4호
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• pp.202-208
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• 2005

The genetic algorithm (GA) which is one of the popular optimum algorithm has been used to solve a variety of optimum problems. Because it need not require the gradient of objective function and is easier to find global solution than gradient-based optimum algorithm using the gradient of objective function. However optimum method using the GA and the finite element method (FEM) takes many computational time to solve the optimum structural design problem which has a great number of design variables, constraints, and system with many degrees of freedom. In order to overcome the drawback of the optimum structural design using the GA and the FEM, the author developed a computer program which can optimize frame structures by using the GA and the generalized transfer stiffness coefficient method. In order to confirm the effectiveness of the developed program, it is applied to optimum design of plane frame structures. The computational results by the developed program were compared with those of iterative design.

• 한국소음진동공학회논문집
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• 제16권5호
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• pp.470-478
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• 2006

An efficient method for change of eigenvectors and eigenvalues due to the modifying proportional damping structure using sensitivity coefficients is presented. Sensitivity coefficients are determined by iteration with eigenvalue and eigenvectors before modification of system. The proposed method is applied to examples of 3 degrees of freedom system and plate by modifying mass and stiffness. The predicted change of eigenvectors and eigenvalues are in a good agreement with these from the structural re-analysis after modification of mass and stiffness.

• 분석과학
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• 제8권4호
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• pp.707-714
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• 1995

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonstrates its excellent utility for the complex depth profile system. It includes the stable restoration of the depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.