• 한국BIM학회 논문집
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• 제9권1호
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• pp.1-10
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• 2019

In process of creating BIM model for tunnel, many user use still CAD, so the workflow for BIM design is not perfect. Therefore, in this paper, we proposes a method to automatically create BIM model without converting 2D drawings in tunnel design. It can allow engineers to design BIM-based tunnel with maximum use of linear information and modify the BIM model whenever there is changed linear information. To do this, we use Dynamo, which can reduce the time required for creating and modifying BIM models during design changes, saving time wasted for BIM conversion design.

• 전자공학회논문지CI
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• 제41권3호
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• pp.79-90
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• 2004

본 논문에서는 퍼지 피드백 선형화 제어 시스템에 대한 체계적인 강인 안정성 해석과 제어기 설계방법을 제안한다. 제어 대상인 비선형 시스템을 모델링 하는데 있어서 Takagi-Sugeno 퍼지 모델 기법을 이용하고, 이때 발생할 수 있는 모델 불확실성과 외란을 고려한다. 모델링을 통해서 얻어진 폐루프 시스템에 대한 안정성 판별은 Diagonal Norm based Linear Differential Inclusions 으로의 구조 변환을 이용하여 강인 안정성 해석을 하였으며, 퍼지 피드백 선형화 제어 시스템을 안정화시키는 제어기의 이득을 얻기 위하여 LMI 최적화 계산법을 기반으로 한 수치 해석법을 제시하였다. 제안된 방법의 효과를 확인하기 위해서 강인 안정성 해석 및 제어 설계에 대한 모의실험을 수행한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.976-979
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• 1996

Teleoperation is the extension of a person's sensing and manipulation capability to a remote location. Teleoperators generally can be modeled as linear transfer function indecently including modeling uncertainty. Modeling uncertainties can make the system unstable and its performance poor. Thus I'm studying about a design framework for a bilateral controller of teleoperator systems with modeling uncertainties. In this paper, a method based on the H$_{\infty}$-optimal control and .mu.-synthesis frameworks are introduced to design a controller for the teleoperator that achieves stability and performance in the presence of the modeling uncertainties..ties.inties.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.373-376
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• 2006

In general, there are three kinds of methods in analyzing dynamic robust design experiment: loss model approach, response function approach, and response model approach. In this talk, we review the three modeling approaches in terms of several criteria in comparison. This talk also generalizes the response model approach based on a generalized linear model. We develop a generalized two-step optimization procedure to substantially reduce the process variance by dampening the effect of both explicit and hidden noise variables. The proposed method provides more reliable results through iterative modeling of the residuals from the fitted response model. The method is compared with three existing approaches in practical examples.

• Journal of Power Electronics
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• 제14권3호
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• pp.572-579
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• 2014

As a non-linear time variant system, the four-quadrant line converter of an electric multiple unit (EMU) was expressed by linear time periodic functions near an operating point and modeled by a steady-state harmonic domain matrix. The components were then combined according to the circuit connection and relations of the feedback control loops to form a complete converter model. The proposed modeling method allows the study of the amplitude of harmonic impedances to explore harmonic coupling. Moreover, the proposed method helps provide a better design for the converter controllers, as well as solves the problem in coordination operation between the EMUs and the AC supply. On-site data from an actual $CRH_2$ high-speed train were used to validate the modeling principles presented in the paper.

• Journal of Biosystems Engineering
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• 제37권4호
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• pp.258-264
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• 2012

Purpose: This review aims at introducing 3 modeling approaches classified into 3 categories based on the purpose (estimation or prediction), structure (linear or non-linear) and phase (steady-state or dynamic-state); 1) statistical approaches, 2) kinetic modeling and 3) mechanistic modeling. We hope that this review can be a useful guide in the model-based approach of calcium metabolism as well as illustrates an application of engineering tools in studying biosystems. Background: The meaning of biosystems has been expanded, including agricultural/food system as well as biological systems like genes, cells and metabolisms. This expansion has required a useful tool for assessing the biosystems and modeling has arisen as a method that satisfies the current inquiry. To suit for the flow of the era, examining the system which is a little bit far from the traditional biosystems may be interesting issue, which can enlarge our insights and provide new ideas for prospective biosystem-researches. Herein, calcium metabolic models reviewed as an example of application of modeling approaches into the biosystems. Review: Calcium is an essential nutrient widely involved in animal and human metabolism including bone mineralization and signaling pathways. For this reason, the calcium metabolic system has been studied in various research fields of academia and industries. To study calcium metabolism, model-based system analyses have been utilized according to the purpose, subject characteristics, metabolic sites of interest, and experimental design. Either individual metabolic pathways or a whole homeostasis has been modeled in a number of studies.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1328-1333
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• 2003

In the present study, an integrated framework of geometric modeling, analysis, and design optimization is proposed. Geometric modeling is based on B-spline surface representation. Geometrically-exact shell finite element is implemented in analysis module. Control points of the surface are selected as design variables for optimization, which can make the interaction easier between analysis and surface representation. Sequential linear programming(SLP) is adopted for the shape optimization of surfaces. For the computation of shape sensitivities, semi-analytical method is used. The developed integrated framework should serve as a powerful tool for the geometric modeling, analysis, and shape design of surfaces.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.765-768
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• 2000

Linearization of the biped dynamic equations and design of linear controller for the linearized equations are studied in this paper. The biped robot with inverted pendulum type trunk, used to stabilize the dynamic balancing of the biped robot during dynamic walking period, is modelled with 14 DOF and simulated. Despite of well defined linear control theories so far, the linear control methods was limited to the applications for a walking robot, because they have been inherently strong nonlinear properties, such as a modeling parameter uncertainties, external forces as noise, inertial and Coriolis terms by three dimensional modeling and so on. To linearize the nonlinear equations of motion of biped robot on MIMO and time varying linear equations of motion, 1st order Taylor series is used to formulate the linear equation. And a 2nd order numerical perturbation method Is used to approximate partial differential equations. Using the linearized equations of motion, a linear controller is designed by pole placement method with feed forward compensation. Using the obtained linearized equations and linear controller, the continuous walking simulation is performed.

• 전자공학회논문지B
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• 제31B권6호
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.