• Communications of the Korean Mathematical Society
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• v.12 no.1
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• pp.165-176
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• 1997

In order to overcome computational ill-posedness which arises when we solve the least square problems, nonlinear smoothing splines are used. The existence and the convergence on nonlinear smoothing spline are shown with numerical experiments.

• Journal of the Korean Mathematical Society
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• v.33 no.4
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• pp.955-982
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• 1996

In surface compression applications, one of the main issues is how to efficiently store and calculate the computer representation of certain surfaces. This leads us to consider a nonlinear approximation by box splines with free knots since, for instance, the nonlinear method based on wavelet decomposition gives efficient compression and recovery algorithms for such surfaces (cf. [12]).

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.479-491
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• 2007

This paper presents a new adaptive observer design method for a class of uncertain nonlinear systems by using spline approximation. This scheme leads to a simplified observer structure which requires only fixed number of integrations, regardless of the number of parameters to be estimated. This benefit can reduce the number of integrations of the observer filter dramatically. Moreover, the proposed adaptive observer automatically generates the required spline elements according to the varying output value and, as a result, does not requires the pre-knowledge of upper and lower bounds of the output. This is another benefit of our approach since the requirement for known output bounds have been one of the main drawbacks of practical universal approximation problems. Both of the benefits stem from the local support property, which is specific to splines.

• Computers and Concrete
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• v.16 no.4
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• pp.569-585
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• 2015

Various computational tools are available for modeling highly nonlinear structural engineering problems that lack a precise analytical theory or understanding of the phenomena involved. This paper adopts a fairly simple nonparametric adaptive regression algorithm known as multivariate adaptive regression splines (MARS) to model the nonlinear interactions between variables. The MARS method makes no specific assumptions about the underlying functional relationship between the input variables and the response. Details of MARS methodology and its associated procedures are introduced first, followed by a number of examples including three practical structural engineering problems. These examples indicate that accuracy of the MARS prediction approach. Additionally, MARS is able to assess the relative importance of the designed variables. As MARS explicitly defines the intervals for the input variables, the model enables engineers to have an insight and understanding of where significant changes in the data may occur. An example is also presented to demonstrate how the MARS developed model can be used to carry out structural reliability analysis.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.17-19
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• 2005

In this paper, using B-splines as universial approximators, we have obtained a plant parametrization which permits the construction of an adaptive observer. The particular property of this parametrization is that the dynamic order of the filters in this design does not depend on the number of parameters in the plant parametrization. This appears to be a beneficial property especially because the number of such parameters tends to be very high for universial approximator based designs.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.331-334
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• 2003

In this paper, using B-splines as universial approximators, we have obtained a plant parametrization which permits the construction of an adaptive observer. The particular property of this parametrization is that the dynamic order of the filters in this design does not depend on the number of parameters in the plant parametrization. This appears to be a beneficial property especially because the number of such parameters tends to be very high for universial approximator based designs.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• Steel and Composite Structures
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• v.33 no.4
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• pp.583-594
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• 2019

In the areas highly exposed to earthquakes, concrete-filled steel tube columns (CFSTCs) are known to provide superior structural aspects such as (i) high strength for good seismic performance (ii) high ductility (iii) enhanced energy absorption (iv) confining pressure to concrete, (v) high section modulus, etc. Numerous studies were reported on behavior of CFSTCs under axial compression loadings. This paper presents an analytical model to predict ultimate load capacity of CFSTCs with circular sections under axial load by using multivariate adaptive regression splines (MARS). MARS is a nonlinear and non-parametric regression methodology. After careful study of literature, 150 comprehensive experimental data presented in the previous studies were examined to prepare a data set and the dependent variables such as geometrical and mechanical properties of circular CFST system have been identified. Basically, MARS model establishes a relation between predictors and dependent variables. Separate regression lines can be formed through the concept of divide and conquers strategy. About 70% of the consolidated data has been used for development of model and the rest of the data has been used for validation of the model. Proper care has been taken such that the input data consists of all ranges of variables. From the studies, it is noted that the predicted ultimate axial load capacity of CFSTCs is found to match with the corresponding experimental observations of literature.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1848-1853
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• 1991

To solve the nonlinear system problems, many methods have been proposed. Generally those methods however need long processing time because of their complicated algorithms. On the other hand, some simple linearization methods also have been studied. In this paper, a new linearization method using cubic splines[1] is proposed. The approximated linear system obtained by this method we can apply the conventional simple linear system theories such as Kalman filter[2, 3] for the estimation problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1133-1137
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• 1995

This paper presents a numerical method of the global search for an optimal geometric path for a manipulator arm amid obstacles. Finite term quintic B-splines are used to describe an arbitrary point-to-point manipulator motion with fixed moving time. The coefficients of the splines span a linear vector space, a point in which uniquely represents the manipulator motion. All feasible geometric paths are searched by adjusting the seed points of the obstacle models in the penetration growth distances. In the numerical implementation using nonlinear programming, the globally optimal geometric path is obtained for a spatial 3-link(3-revolute joints) manipulator amid several hexahedral obstacles without simplifying any dynamic or geometric models.