• 한국정보디스플레이학회:학술대회논문집
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• 2003.07a
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• pp.32-35
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• 2003

Nonlinear parameterization of OLED device from measurements of bias dependence of impedance spectra and parameter extraction using Levenberg-Marquardt complex nonlinear least square regression algorithm based on resistor-capacitor equivalent circuit model enables computer simulation of OLED power driving characteristics in forms of square-wave or sinusoidal output signal at arbitrary conditions. We introduce developed OLED power driving simulation software and discuss transient responses in voltage-or current-controlled operations as well as nonlinear characteristics of OLED, by presenting both the simulation and experimental results. This OLED simulation technique using impedance spectroscopy is extremely useful in predicting performance of the nonlinear device, especially in time-domain analysis of device operation.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.326-328
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• 1993

Modelling theory, based on differential equations, is not an adequate tool for solving the problems of complex system. Identification of complex system using GMDH(group method of data handling) is more appropriate for this problems. In this paper, GMDH algorithm is used to identify the nonlinear plant and to design model following nonlinear control system. Simulation for the DC motor show the good performance of model following nonlinear control system.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.263-269
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• 1998

We use the slope bounded saturation nonlinear feedback element instead of relay to find ultimate gain and period of linear plant. Saturation nonlinear element reduces the high harmonics of plant output. The reduction of high harmonics improve the accuracy of describing function method used to find ultimate gain and period. We give a simple procedure to find ultimate gain and period with saturation nonlinear element. A PID controller design method with known time delay element is also given, which is very useful when oscillation is not occurred with nonlinear element.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.1-33
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• 2001

We address a novel approach to identify a nonlinear dynamic system for Wiener models, which are composed of a linear dynamic system part followed by a nonlinear static part. The aim of system identification here is to provide the optimal mathematical model of both the linear dynamic and the nonlinear static parts in some appropriate sense. Assuming the nonlinear static part is invertible, we approximate the inverse function by a piecewise linear function. We estimate the piecewise linear inverse function by using the evolutionary computation approach such as genetic algorithm (GA) and evolution strategies (ES), while we estimate the linear dynamic system part by the least squares method. The results of numerical simulation studies indicate the usefulness of proposed approach to the Wiener model identification.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.540-545
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• 2012

In this paper, we propose a fault diagnosis method using artificial neural network and SVM (Support Vector Machine) to detect and isolate faults in the nonlinear systems. The proposed algorithm consists of two main parts: fault detection through threshold testing using a artificial neural network and fault isolation by SVM fault classifier. In the proposed method a fault is detected when the errors between the actual system output and the artificial neural network nominal system output cross a predetermined threshold. Once a fault in the nonlinear system is detected the SVM fault classifier isolates the fault. The computer simulation results demonstrate the effectiveness of the proposed SVM and artificial neural network based fault diagnosis method.

• Structural Engineering and Mechanics
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• v.58 no.6
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• pp.1109-1126
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• 2016

The present paper focuses on size optimization of double layer barrel vaults considering nonlinear behavior. In order to tackle the optimization problem an improved colliding bodies optimization (ICBO) algorithm is proposed. The important task that should be achieved before optimization of structural systems is to determine the best form having the least cost. In this study, an attempt is done to find the best form then it is optimized considering linear and non-linear behaviors. In the optimization process based on nonlinear behavior, the geometrical and material nonlinearity effects are included. A large-scale double layer barrel vault is presented as the numerical example of this study and the obtained results indicate that the proposed ICBO has better computational performance compared with other algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.236-242
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• 1992

Multi-layered neural networks are applied to the identification and control of nonlinear dynamical system. Traditional adaptive control techniques can only deal with linear systems or some special nonlinear systems. A scheme for combining multi-layered neural networks with model reference network techniques has the capability to learn the nonlinearity and shows the great potential for adaptive control. In many interesting cases the system can be described by a nonlinear model in which the control input appears linearly. In this paper the identification of linear and nonlinear part are performed simultaneously. The projection algorithm and the new estimation method which uses the delta rule of neural network are compared throughout the simulation. The simulation results show that the identification and adaptive control schemes suggested are practically feasible and effective.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.248-254
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• 2000

This paper presents and output feedback fuzzy H(sup)$\infty$ control problem for a class of nonlinear systems with time-varying delayed state. The Takagi-Sugeno fuzzy model is employed to represent a nonlinear systems with time-varying delayed state. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of fuzzy H(sup)$\infty$ controllers are given in terms of matrix inequalities. Constructive algorithm for design of fuzzy H(sup)$\infty$ controller is also developed. A simulation example is given to illustrate the performance of the proposed design method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.514-519
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• 2006

This paper presents a new nonlinear analysis algorithm which uses the equivalent nodal load for the element stiffness. The equivalent nodal load represents the influence of the stiffness change such as the addition of elements, the deletion of elements, and/or the partial change of element stiffness. The nonlinear analysis of structures using the equivalent load improves the efficiency very much because the inverse of the structural stiffness matrix, which needs a large amount of computation to calculate, is reused in each loading step. In this paper, the concept of nonlinear analysis using the equivalent load for the element stiffness is described and some numerical examples are provided to verify it.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.1
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• pp.11-20
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• 2017

This study investigates the seismic performance of solid reinforced concrete columns with triangular reinforcement details using nonlinear seismic analysis. The developed reinforcement details are economically feasible and rational, and facilitate shorter construction periods. By using a sophisticated nonlinear finite element analysis program, the accuracy and objectivity of the assessment process can be enhanced. Solution of the equations of motion is obtained by numerical integration using Hilber-Hughes-Taylor (HHT) algorithm. The proposed numerical method gives a realistic prediction of seismic performance throughout the input ground motions for several column specimens. As a result, developed triangular reinforcement details were designed to be superior to the existing reinforcement details in terms of required performance.