• 동력기계공학회지
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• 제12권2호
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• pp.62-70
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• 2008

The paper made a description of the method for numerical analysis and modeling of a proportional pressure control valve by bondgraph. The valve is a three port pressure regulator valve, consists of two subsystems; a proportional solenoid and a spool assembly. A purpose of this study is to analysis the dynamic characteristics of the valve using bondgraph method and to verified results that each of parameters has an effect on modeling. It considered the effect which the presence of solenoid, flow coefficient and non-linearity of resistance causes in the valve modeling. In particular, it is analyzed the effect that the solenoid interacted with modeling results and characteristics of the nonlinear resistance through orifice on the supply and discharge side of valve. Thus this paper described method to present nonlinear characteristics by bondgraph modeling method, so that we could know easily result that each parameters has an effect on the modeling.

• Environmental Engineering Research
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• 제14권2호
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• pp.102-110
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• 2009

Application of artificial intelligence (AI) approaches in eco-environmental modeling has gradually increased for the last decade. Comprehensive understanding and evaluation on the applicability of this approach to eco-environmental modeling are needed. In this study, we reviewed the previous studies that used AI-techniques in eco-environmental modeling. Decision Tree (DT) and Artificial Neural Network (ANN) were found to be major AI algorithms preferred by researchers in ecological and environmental modeling areas. When the effect of the size of training data on model prediction accuracy was explored using the data from the previous studies, the prediction accuracy and the size of training data showed nonlinear correlation, which was best-described by hyperbolic saturation function among the tested nonlinear functions including power and logarithmic functions. The hyperbolic saturation equations were proposed to be used as a guideline for optimizing the size of training data set, which is critically important in designing the field experiments required for training AI-based eco-environmental modeling.

• 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.

• Computers and Concrete
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• 제33권6호
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• pp.725-738
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• 2024

This study presents a macro-modeling procedure for nonlinear finite element analysis of reinforced and prestressed concrete panels under blast loading. The analysis procedure treats cracked concrete as an orthotropic material based on a smeared rotating crack model within the context of total-load secant stiffness-based formulation. A direct time integration method compatible with the analysis formulation is adapted to solve the dynamic equation of motion. Considerations are made to account for strain rate effects. The analysis procedure is verified by modeling 14 blast tests from various sources reported in the literature including a blast simulation contest. The analysis results are compared against those obtained from experiments, simplified single-degree-of-freedom (SDOF) methods, and sophisticated hydrocodes. It is demonstrated that the smeared crack macro-modeling approach is a viable alternative analysis procedure that gives more information about the structural behavior than SDOF methods, but does not require detailed micro-modeling and extensive material characterization typically needed with hydrocodes.

• 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.

• 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.

• Smart Structures and Systems
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• 제29권5호
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• pp.693-703
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• 2022

This study investigates an effective approach to stabilize nonlinear systems. To ensure the asymptotic nonlinear stability in nonlinear discrete-time systems, the present study presents controller for an EBA (Evolved Bat Algorithm) NN (fuzzy neural network) in the algorithm. In fuzzy evolved NN modeling, the auxiliary circuit with high frequency LDI (linear differential inclusions) and NN model representation is developed for the nonlinear arbitrary dynamics. An example is utilized to demonstrate the system more robust compared with traditional control systems.

• Structural Engineering and Mechanics
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• 제46권2호
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• pp.213-229
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• 2013

Although performance based assessment procedures are mainly developed for reinforced concrete and steel buildings, URM (Unreinforced Masonry) buildings occupy significant portion of buildings in earthquake prone areas of the world as well as in IRAN. Variability of material properties, non-engineered nature of the construction and difficulties in structural analysis of masonry walls make analysis of URM buildings challenging. Despite sophisticated finite element models satisfy the modeling requirements, extensive experimental data for definition of material behavior and high computational resources are needed. Recently, nonlinear equivalent frame models which are developed assigning lumped plastic hinges to isotropic and homogenous equivalent frame elements are used for nonlinear modeling of URM buildings. The equivalent frame models are not novel for the analysis of masonry structures, but the actual potentialities have not yet been completely studied, particularly for non-linear applications. In the present paper an effective tool for the non-linear static analysis of 2D masonry walls is presented. The work presented in this study is about performance assessment of unreinforced brick masonry buildings through nonlinear equivalent frame modeling technique. Reliability of the proposed models is tested with a reversed cyclic experiment conducted on a full scale, two-story URM building at the University of Pavia. The pushover curves were found to provide good agreement with the experimental backbone curves. Furthermore, the results of analysis show that EFM (Equivalent Frame Model) with Dolce RO (rigid offset zone) and shell element have good agreement with finite element software and experimental results.

• Advances in Computational Design
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• 제8권2호
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• pp.97-112
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• 2023

The Finite Element (FE) modeling of Reinforced Concrete (RC) under seismic loading has a sensitive impact in terms of getting good contribution compared to experimental results. Several idealized model types for simulating the nonlinear response have been developed based on the plasticity distribution alone the model. The Continuum Models are the most used category of modeling, to understand the seismic behavior of structural elements in terms of their components, cracking patterns, hysteretic response, and failure mechanisms. However, the material modeling, contact and nonlinear analysis strategy are highly complex due to the joint operation of concrete and steel. This paper presents a numerical simulation of a chosen RC column under monotonic and cyclic loading using the FE Abaqus, to assessthe hysteretic response and failure mechanisms in the RC columns, where the perfect bonding option is used for the contact between concrete and steel. While results of the numerical study under cyclic loading compared to experimental tests might be unsuccessful due to the lack of bond-slip modeling. The monotonic loading shows a good estimation of the envelope response and deformation components. In addition, this work further demonstrates the advantage and efficiency of the damage distributions since the obtained damage distributions fit the expected results.

• 한국전자파학회논문지
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• 제21권11호
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• pp.1220-1228
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• 2010

본 논문에서는 비선형 RF 전력 증폭기의 효율적인 다항식 기반의 이산 신호 모델링 방법을 제시하였다. 비선형 RF 증폭기의 입, 출력 신호의 샘플링 과정을 통하여 이산 비선형 모델을 추출하는 과정을 기술하고, 테일러 급수와 메모리 다항식 구조를 이용한 다항식 기반의 비선형 이산 모델에서 모델 인자인 샘플률, 비선형 차수, 최대 메모리 깊이의 변화에 따른 모델의 오차를 분석하였다. 다항식 기반의 비선형 모델에서 오차는 샘플률, 비선형 차수, 최대 메모리 깊이에 대하여 특정 값 이후부터 일반적으로 수렴하는 특성을 보인다. 이에 모델 인자값에 따른 시스템의 복잡성을 고려하는 효율적인 이산 신호 모델링 기법을 제시하였다. 모델링 효율 지수를 정의하고, 이를 활용하여 최적의 모델 인자 값을 추출하는 방법을 제시하였다. 제시한 방법을 WiBro, WCDMA 등의 다양한 신호를 가지는 RF 전력 증폭기의 모델링에 적용하고, 제시한 방법의 효율성을 검증하였다. 제안된 기법은 빠른 속도의 모델링과 저렴한 가격의 디지털부를 사용할 수 있게 하여 차후 광대역 송신기에서의 빠른 속도와 낮은 가격의 디지털 전치 왜곡기 구성 등에 활용될 수 있을 것으로 사료된다.