• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.75-78
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• 2004

In an optical disk drive, a feeding system which is used to move the optical pick-up system to the target position and the proper control scheme of it are important in random access performance. Since the effect of control is directly affected by the modeling precision of the real system, the precise modeling to the real system should be acquired. Although a simple linear order modeling to the feeding system of an optical disk drive is useful in understanding of the overall dynamic characteristics, the dynamic characteristics which are belongs to the nonlinear area cannot be predicted correctly. Furthermore, the feeding system of an optical disk drive has many nonlinear characteristics such as a nonlinear friction and backlash. For this reason, the understanding of the nonlinear properties in the feeding system is very important. In this paper, the nonlinear items of the feeding system, friction and backlash, are introduced and the effect of it are investigated. Finally, the mathematical model considering the nonlinear properties is compared to the real system, and some comments of it are given.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.151-154
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• 2001

The pneumatic vibration isolation systems have been widely used in industry and laboratories, but the full mathematical analysis and nonlinear modeling techniques have not been reported yet, even while the nonlinear features of the pneumatic vibration isolation system decide the main characteristics. For instance, the orifice in a pneumatic vibration isolator has been traditionally considered as a simple viscous damper, which was too much simplified to explain the performance of the isolation system. In this paper, the nonlinear characteristics are considered for the orifice and chamber, etc. The numerical simulation is carried out by the MATLAB/Simulink software. From the analysis result, a clear trend of the nonlinear features is shown: the vibration transmissibility changes not only due to the excitation frequency but also due to the amplitude of the vibration excitation. Therefore various design parameters are optimally chosen for the vibration isolation system. The proposed methods show good compatibility between the analysis results and the experiments.

• 한국정밀공학회지
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• 제13권12호
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• pp.22-29
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• 1996

In this paper the nodes of the multilayer hidden layers have been modified for modeling the nonlinear systems. The structure of nodes in the hidden layers is built with the feedforward, the cross talk and the recurrent connections. The feedforward links are mapping the nonlinear function and the cross talks and the recurent links memorize the dynamics of the system. The cross talks are connected between the modes in the same hidden layers and the recurrent connection has self feedback, and these two connections receive one time delayed input signals. The simplified steam boiler and the analytic multi input multi output nonlinear system which contains process noise have been modeled using this neural networks.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.100-103
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• 2008

Recently Development of construction system that subjective operators share and control information efficiently based on the three-dimensional space and design information throughout life cycle of construction project is progressing dynamically. In case of civil structures which are infrastructure, Demand for structure of complex system which has multi-functions such as super and smart bridges and express rails is increasing and system development which computerizes and integrates process of structure design is in need. For that, research about link way between three dimensional modeling data and structure analysis programs should be preceded. In this research, therefore, research about interface design between three dimensional virtual modeling data to automate efficient civil-structure-design and nonlinear finite element analysis program which is made up of reinforced concrete material model that express material's character clearly.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.18-21
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• 1996

Even though there are several deterministic methods for the modeling of linear systems, there is no standard method for the modeling of nonlinear systems. For the modeling of nonlinear systems we have applied the genetic programming method to estimate nonlinear time sereis. We get the time series from the simple known nonlinear dynamics, and fed those to genetic programming. For the tested nonlinear systems, suggested method estimated the nonlinear dynamics correctly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2034-2036
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• 2002

In this paper, we propose the modeling of a chaotic nonlinear system using wavelet neural networks. In our modeling, we used the parameter adjusting method as the training method of a wavelet neural network. The difference between the actual output of a nonlinear chaotic system and that of a wavelet neural network adjusts the parameters of a wavelet neural network using the gradient-descent method. To verify the efficiency of this paper, we perform the simulation using Duffing system, which is a representative continuous time chaotic nonlinear system.

• 한국지능시스템학회논문지
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• 제14권2호
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• pp.190-194
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• 2004

본 논문에서는 비선형 생화학적인 공정의 모델링을 위해 퍼지시스템이 응용된 것을 보인다. SBR 반응조에서 질소제거를 위한 수처리 공정이 제시되었으며, 이 공정의 ORP값을 모델링하고 동정하기 위해 서로 다른 후반부 다항식을 가진 퍼지시스템이 소개되었다. 퍼지모델링 결과를 비교하고 분석하며 또한 제안된 방법에 의해 비선형 공정이 합리적이고 효율적으로 모델링 될 수 있음을 본 논문에서 보인다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.371-374
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• 1999

This paper present the nonlinear control and the Lyapunov analysis of the nonlinear electro-hydraulic system for steering control of UCT. Electro-hydraulic system itself has the high nonlinearities arisen from the nonlinear characteristics of the pressure-fluid flow in valve and friction in cylinder. These nonlinearities are unmodeled terms in the transfer function. This paper presents the system modeling, analysis of stability based on the Lyapunov function and simulation of the nonlinear hydraulic servo system.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.