• Proceedings of the Korean Society of Rheology Conference
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• 2002.11a
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• pp.101-103
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• 2002

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.957-960
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• 1995

A new method is introduced for the parametrization in B-spline surface interpolation. THis method uses the basis function to assign the parameter values to the arbitrary set of geometric data. This method gives us several important advantages in geometric modeling.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1151-1154
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• 1993

The purpose of the paper is to explain some heuristic, common sense suppositions of fuzzy control. It is shown that Fuzzy Control is a kind of quasilinear interpolation of prototypes. Control function can be sufficiently exact represented as piecewise-linear function. The best interpolation is connected with normalized intersected fuzzy sets.

• Communications of the Korean Mathematical Society
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• v.23 no.2
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• pp.295-305
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• 2008

This paper demonstrates how composite-exponential-fitting interpolation rules can be constructed to fit an oscillatory function using not only pointwise values of that function but also of that functions's derivative on a closed and bounded interval of interest. This is done in the framework of exponential-fitting techniques. These rules extend the classical composite cubic Hermite interpolating polynomials in the sense that they become the classical composite polynomials as a parameter tends to zero. Some examples are provided to compare the newly constructed rules with the classical composite cubic Hermite interpolating polynomials (or recently developed interpolation rules).

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1810-1815
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• 2003

Sliding mode control with nonlinear interpolation in the boundary layer is proposed. A modified sigmoid function is used for nonlinear interpolation in the boundary layer and its parameter is tuned by a fuzzy logic controller. The fuzzy logic controller that takes the distance between the system state and the sliding surface as its input guides the choice of parameter of the modified sigmoid function and the parameter is on-line tuned. Owing to the decreased thickness, the proposed method has better tracking performance than the conventional linear interpolation method. To demonstrate its performance, the proposed control algorithm is applied to a simple nonlinear system model.

• Structural Engineering and Mechanics
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• v.21 no.3
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• pp.315-332
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• 2005

The Element-free Galerkin Method has become a very popular tool for the simulation of mechanical problems with moving boundaries. The internally applied Moving Least Squares interpolation uses in general Gaussian or cubic weighting functions and has compact support. Due to the approximative character of this interpolation the obtained shape functions do not fulfill the interpolation conditions, which causes additional numerical effort for the application of the boundary conditions. In this paper a new weighting function is presented, which was designed for meshless shape functions to fulfill these essential conditions with very high accuracy without any additional effort. Furthermore this interpolation gives much more stable results for varying size of the influence radius and for strongly distorted nodal arrangements than existing weighting function types.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.31-38
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• 1994

This paper presents an improved interpolation algorithm which enables to find a unit function in $H^{\infty}$. From the proposed algorithm the interpolation problem on the infinity point with multiplicity can be solved. This is based on the DPL algorithm the acquired unit function has low order and can be directly applied to strong/simultaneous stabilization problem in control systems. Finally, we verify that poles of transfer function of closed-loop system exist in stable region while investgating internal stability.

• Kyungpook Mathematical Journal
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• v.58 no.3
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• pp.453-462
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• 2018

In this paper, we present a symbolic formulation of the error obtained due to an approximation of a given function by the mixed-interpolating function. Using the proposed symbolic method, we compute the error evaluation operator as well as the error estimation at any arbitrary point. We also present an algorithm to compute an approximation of a function by the mixed interpolation technique in terms of projector operator. Certain examples are presented to illustrate the proposed algorithm. Maple implementation of the proposed algorithm is discussed with sample computations.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.164.2-164
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• 2001

Sliding mode control (SMC) with variable nonlinear boundary layer is proposed. Two Fuzzy logic controllers (FLCs) are used to decide both boundary layer thickness and nonlinear interpolation using sigmoid function in the boundary layer. The nonlinear interpolation in the boundary layer suing FLC reduces stead state error and chattering. Sigmoid function is used to nonlinear interpolation in the boundary layer sigmoid function parameter with FLC. To demonstrate its performance, the Proposed control algorithm is applied to a simple nonlinear system.

• Structural Engineering and Mechanics
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• v.11 no.2
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• pp.221-236
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• 2001

A local point interpolation method (LPIM) is presented for the stress analysis of two-dimensional solids. A local weak form is developed using the weighted residual method locally in two-dimensional solids. The polynomial interpolation, which is based only on a group of arbitrarily distributed nodes, is used to obtain shape functions. The LPIM equations are derived, based on the local weak form and point interpolation. Since the shape functions possess the Kronecker delta function property, the essential boundary condition can be implemented with ease as in the conventional finite element method (FEM). The presented LPIM method is a truly meshless method, as it does not need any element or mesh for both field interpolation and background integration. The implementation procedure is as simple as strong form formulation methods. The LPIM has been coded in FORTRAN. The validity and efficiency of the present LPIM formulation are demonstrated through example problems. It is found that the present LPIM is very easy to implement, and very robust for obtaining displacements and stresses of desired accuracy in solids.