• Fibers and Polymers
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• v.6 no.4
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• pp.348-354
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• 2005

These days consumers' various demands are accelerating research on apparel manufacturing system including automatic measurement, pattern generation, and clothing simulation. Accordingly, methods of reconstructing human body from point-clouds measured using a three dimensional scanning device are required for apparel CAD system to support these functions. In particular, we present in this study a human body reconstruction method focused on two issues, which are the decision of the number of control point for each sectional curve with error bound and the local knot removal for reducing the unusual concentration of control points. The approximation of sectional curves with error bounds as an approximation criterion leads all sectional curves to their own particular shapes apart from the number of control points. In addition, the application of the local knot removal to construction of human body sectional curves reduces the unusual concentration of control points effectively. The results may be used to produce an apparel CAD system as an automatic pattern generation system and a clothing simulation system through the low level control of NUBS or NURBS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.9
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• pp.2731-2743
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• 1996

When modeling error is large of plant is time-varying, it is hard to obtain good robust performance and robust stability by conventional contorl methods. Here, we need to design a robust controller bearing modeling error. In this paper, based on recently developed Time Delay Control(TDC) and Disturbance Observer the output feedback Robust Disturbance Observer(RDO), which is easily combined with general linear control, is proposed. Proposed RDO is derived from extending the main idea of Disturbance Observer to multi-input multi-output linear system. RDO solves robust stability problem of Disturbance Observer and has the robust performance same as nominal performance. RDO controlled dual stage positioning system shows excellent robust performance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.158-159
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• 2016

This paper aims to analyze design errors prevented by building information modeling (BIM)-based design validation to identify consideration factors for successfully implementing BIM-based design validation in the architecture, engineering, and construction (AEC) projects. More than 1,300 design errors detected by BIM-based design validation in three BIM-based projects in South Korea are categorized according to its causes, work types, and likelihoods to cause project delay and cost overrun. Each design error is analyzed by conducting face-to-face interviews with practitioners in the three projects.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.431-431
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• 2000

The modeling of 5-bar linkage robot manipulator dynamics by means of a mathematical and neural architecture is presented. Such a model is applicable to the design of a feedforward controller or adjustment of controller parameters. The inverse model consists of two parts: a mathematical part and a compensation part. In the mathematical part, the subsystems of a 5-bar linkage robot manipulator are constructed by applying Kawato's Feedback-Error-Learning method, and trained by given training data. In the compensation part, MLP backpropagation algorithm is used to compensate the unmodeled dynamics. The forward model is realized from the inverse model using the inverse of inertia matrix and the compensation torque is decoupled in the input torque of the forward model. This scheme can use tile mathematical knowledge of the robot manipulator and analogize the robot characteristics. It is shown that the model is reasonable to be used for design and initial gain tuning of a controller.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.788-791
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• 2002

The Timoshenko beam model has been acknowledged as the most accurate model for representing beam structures. However, the Timoshenko beam model may give rise to significant error when it is applied to multi-stepped beam structures. This paper is intended to demonstrate and improve the modeling error of Timoshenko beam theory for multi-stepped team structures. A tentative bending spring is introduced to represent the stiffness change around a step in beams. This paper proposes a finite element modeling method in the light with the bending spring. The proposed method is rigorously compared with commercial finite element codes. The validity of the proposed method is also demonstrated through an experiment..

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.234-238
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• 1996

In this paper, Plasma-Enhanced Chemical Vapor Deposition (PECVD) modeling using Polynomial Neural Networks (PNN) has been introduced. The deposition of SiO2 was characterized via a 25-1 fractional factorial experiment, was used to train PNNs using predicted squared error (PSE). The optimal neural network structure and learning parameters were determined by means of a second fractional factorial experiment. The optimized networks minimized both learning and prediction error. From these PNN process models, the effect of deposition conditions on film properties has been studied. The deposition experiments were carried out in a Plasma Therm 700 series PECVD system. The models obtained will ultimately be used for several other manufacturing applications, including recipe synthesis and process control.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.19-24
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• 1997

In this study, we extend the application of the interface-matrix(IM) method for reflector modeling to Analytic Flux Expansion Nodal (AFEN) method. This include the modifications of the surface-averaged net current continuity and the net leakage balance conditions for IM method in accordance with AFEN fomular. AFEN-interface matrix (AFEN-IM) method has been tested against ZION-1 benchmark problem. The numerical result AFEN-IM method shows 1.24% of maximum error and 0.42% of root-mean square error in assembly power distribution, and 0.006%Δk of neutron multiplication factor. This result proves that the interface-matrix method for reflector modeling can be useful in AFEN method.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.20-24
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• 1995

In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.7-9
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• 2015

Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.