• 전기학회논문지
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• 제57권1호
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• pp.102-108
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• 2008

This paper presents robust and adaptive control method for complicated three dimensional crane systems with uncertain effect. We consider an overhead crane system in which a trolly located on its top is moved to x- and y-axis independently. We first approximate the complicated crane model through linearization approach to simply construct a PD control and then design an adaptive control system for compensating modeling error and control deviation which is feasibly occurred due to system perturbation in practice. An adaptive control scheme is analytically derived using Lyapunov stability theory for a given bound of system perturbation. We accomplish numerical simulation for evaluation of the proposed control system and demonstrate its superiority comparing with the traditional control strategy.

• 통합자연과학논문집
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• 제3권3호
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• pp.162-167
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• 2010

A pseudoreceptor combines structure-based and ligand-based techniques to represent a unifying concept for both receptor mapping and ligand matching. In this molecular modeling approach, there are opportunities to construct the pseudoreceptor models using a set of small molecules. To build a reliable pseudoreceptor model, we need a set of ligand molecules with known affinity (biological activity) to generate 3D bioactive conformation for each of these ligand molecules. Several software packages are available to generate a pseudoreceptor model and this can provide an entry point for structure based drug discovery in cases where receptor structure information is not available. In this review, we presented the concept of pseudoreceptor, as well as discussed about various software packages available to generate a pseudoreceptor model.

• 한국지능시스템학회논문지
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• 제8권5호
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• pp.61-71
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• 1998

Genetic Algorithm(GA) is a method of approaching optimization problems by modeling and simulating the biological evolution. GA needs large time-consuming, so ti had better do on a parallel computer architecture. Our proposed system has a VLSI-oriented interconnection network, which is constructed from a viewpoint of fractal geometry, so that self-similarity is considered in its configuration. The approach to Parallel Genetic Algorithm(PGA) on our proposed system is explained, and then, we construct the classifier system such that the set of samples is classified into weveral classes based on the features of each sample. In the process of designing the classifier system, We have applied PGA to the Traveling Salesman Problem and classified the sample set in the Euclidean space into several categories with a measure of the distance.

• Journal of Mechanical Science and Technology
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• 제20권5호
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• pp.591-601
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• 2006

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.390-393
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• 1997

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• International Journal of Fluid Machinery and Systems
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• 제9권3호
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• pp.265-276
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• 2016

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

• 한국분무공학회지
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• 제22권3호
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• pp.137-145
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• 2017

This paper describes numerical modeling of transcritical and supercritical fluid flows within a liquid propellant rocket engine. In the present paper, turbulence is modeled by standard $k-{\varepsilon}$ model. A conserved scalar approach in conjunction with multi-environment probability density function model is used to account for the turbulent mixing of real-fluids in the transcritical and supercritical region. The two real-fluid equations of state and dense-fluid correction schemes for mixtures are used to construct thermodynamic data library based on the conserved scalar. In this study, calculations are made on two cryogenic nitrogen jets under different chamber pressures. Sensitivity analysis for two different real-fluid equations of sate is particularly emphasized. Based on numerical results, precise structures of cryogenic nitrogen jets are discussed in detail. Numerical results show that the current real-fluid model can predict the essential features of the cryogenic liquid nitrogen jets.

• 한국과학교육학회지
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• 제17권3호
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• pp.301-311
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• 1997

The purpose of this study is to construct a structural equation model and to analyze causal relationships among variables related to attitudes to science using structural equation modeling(SEM) with LISREL VII. The sample consisted of 483 10th grade boys from a general high school in Pusan, Korea. The questionnaires (ABC-attitude scale: affection, behavioral intention, cognition scale of attitude towards science) were developed by the researcher through a pilot study. And other instruments have modified previous ones. Five instruments were used in this study: GALT(group assessment of logical thinking), MTSlS(modified test of science inquiry skill), ABC-attitude scale, MSAS(modified scientific attitude scale), CSAT(common science achievement test). Structural equation modeling with LISREL VII($J\ddot{o}reskog$ & $S\ddot{o}rbom,$ 1993) was employed to estimate the causal inferences about hypothesized relationships among observed data sets. Three competing models consisted of five latent variable(scientific thinking ability, science inquiry skill, attitude towards science, scientific attitude, science achievement) - lP(inquiry preceding) model, AP(attitude preceding) model and AM(attitude mediating) model - were developed. Among these competing models, IP model satisfied the observed data sets. The causal relationships among "attitudes to science" and other latent variables were reliably identified. According to the results of the present study, science inquiry skill was the most significant variable that can predict science achievement. But scientific thinking ability has not directly influenced science achievement. This study suggests that inquiry based teaching-learning processes should be offered to students for improvement of science achievement. At the same time, it seems to be important to develop positive attitude towards science. Understanding of relationships among variables related to attitudes to science will be helpful to the development of science curriculum and to the design of science teaching and learning process. LISREL has been recognized as a useful approach in testing a SEM. However, in this study, LISREL approach was estimated as much more useful method for research design.

• 한국문헌정보학회지
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• 제32권3호
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• pp.143-156
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• 1998

이 논문은 미국 초중고교 교사들을 이용 대상자로 인터넷 상에 산재해 있는 강의안 및 교육자료의 메타데이터 DB를 구축한 GEM 프로젝트에 대한 보고이다. GEM 프로젝트에서는 현재 거의 표준으로 간주되는 더블린 코어의 15개 요소(Elements)를 채택하였고, 여기에 8개 요소를 첨가하여 검색을 원활히 하고자 하였다. GEM 메타데이터 DB의 구축에는 메타데이터 요소들간의 관계를 좀 더 명확히 표현할 수 있는 개념적 데이터 마들링을 사용하였고 메타데이터는 Sybase라는 관계형 데이터베이스에 저장했으며, 이 DB에 웹 인터페이스를 장착하는데에는 Microsoft 액티브 서버 페이지 (ASP) 기술을 이용하였다. GEM 메타데이터의 실제목록은 미국 전역에서 참가하고있는 컨소시엄 회원들에 의해서 이뤄지고 있으며, 그 결과는 인터넷을 통해 Sybase 관계형 데이터베이스에 자동적으로 입력된다. 이 논문에서는 더블린코어, GEM의 개념 및 논리 스키마들을 제시하는 한편, 메타데이터 DB의 구축에 개념적 데이터 마들링을 사용함으로써 얻어지는 장점들을 논하였다. GEM 프로토타입 시스템이 가동되고 있는 URL은 다음과 같다: http://lis.skku.ac.kr/gem/.