• Structural Engineering and Mechanics
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• 제30권1호
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• pp.21-36
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• 2008

The static response of a finite beam resting on a tensionless Pasternak foundation and subjected to a concentrated vertical load is assessed in this study. The concentrated vertical load may be applied at the center of the beam, or it may be offset from the center. The tensionless character of the foundation results in the creation of lift-off regions between the beam and the foundation. An analytical/ numerical solution is obtained from the governing equations of the contact and lift-off regions to determine the extent of the contact region. Although there is no nonlinear term in the equations, the problem shows a nonlinear character since the contact region is not known in advance. Due to that nonlinearity, the essentials of the problem (the coordinates of the lift-off points) are calculated numerically using the Newton-Raphson technique. The numerical results are presented in figures to illustrate the behaviours of the free-free and pinned-pinned beams under symmetric or asymmetric loading. The figures illustrate the effects of the shear foundation parameter and the symmetric and asymmetric loading options on the variation of the contact lengths and the displacement of the beam.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.413-415
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• 2001

In this paper, Polynomial Neural Networks(PNN) is proposed to overcome some problems, such as the conflict between overfitting and good generation, and low reliability and to control nonlinearity and unknown parameter of complex system. PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be generated according to the system environments. The performances depend on two factors, number of inputs and order of polynomials in each node directly. In most cases these factors are decided by the trial and error of designer so optimization is needed in deciding procedure of the factors. Evolutionary algorithm is applied to decide the factors in PNN. The study is illustrated with the aid of representative time series data for gas furnace process used widely for performance comparison, and shows the designed PNN architecture with evolutionary algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.43-48
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• 2002

This paper discusses the application of fuzzy-ARTMAP neural network to compensate the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is the class of ART(adaptive resonance theory) architectures designed fur supervised loaming. It has capabilities not fecund in other neural network approaches, that includes a small number of parameters, no requirements fur the choice of initial weights, automatic increase of hidden units, and capability of adding new data without retraining previously trained data. By a match tracking process with vigilance parameter, fuzzy-ARTMAP neural network achieves a minimax teaming rule that minimizes predictive error and maximizes generalization. Thus, the system automatically leans a minimal number of recognition categories, or hidden units, to meet accuracy criteria. As a input-converting process for implementing fuzzy-ARTMAP equalizer, the sigmoid function is chosen to convert actual channel output to the proper input values of fuzzy-ARTMAP. Simulation studies are performed over satellite nonlinear channels. QPSK signals with Gaussian noise are generated at random from Volterra model. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP equalizer.

• 한국정밀공학회지
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• 제9권3호
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• pp.73-82
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• 1992

An industrial robot, installed real manufacturing processes an element of the system autmation, can be considered as an uncertain system due to dynamic uncertainties in inertial parameters and varying payloads. Most difficuties in controlling a robot manipulator are caused by the fact that the dynamic equations describing the motions of the manipulator are inherently nonlinear and heavily coupled effects between joints and associated links. Existing robot conrol systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severly limited in range of application, speed of operation and variation of payload. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the desinger. The proposed manipulator studied has two loops, an inner loop of model reference adaptive controller and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstailiy approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in practical working environment, various load variations and parameter uncertainties.

• 한국정밀공학회지
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• 제30권8호
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• pp.831-838
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• 2013

This paper focused on the design of an efficient temperature controller for a plant with a wide range of operating temperatures. The greater the temperature difference a plant has, the larger the nonlinearity it is exposed to in terms of heat transfer. For this reason, we divided the temperature range into five sections, and each was modeled using ARMAX(auto regressive moving average exogenous). The movement of the dominant poles of the sliced system was analyzed and, based on the variation in the system parameters with temperature, optimal control parameters were obtained through simulation and experiments. From the configurations for each section of the temperature range, a temperature-based gain-scheduled controller (TBGSC) was designed for parameter variation of the plant. Experiments showed that the TBGSC resulted in improved performance compared with an existing proportional integral derivative (PID) controller.

• 한국정밀공학회지
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• 제7권4호
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• pp.85-102
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• 1990

Up to now, most robot control systems are very naive. They consist of a number of independent position-servo loops to control each joint angle separately. Those control systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severely limited in range of application, speed of operation and variation of payload. This study proposed a new method to design a robot manipulator controller capable of tracking the reference trajectories of joint angles in a reasonable accuracy to cope with actual situations of varying payload, uncertain parameters. The adaptive model following control method has been used to improve existing robot manipulator controllers. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the designer. The stability of adaptive controller is based on the Second Method of Lyapunov. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance under various load varia- tion and parameter uncertainties.

• 대한기계학회논문집A
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• 제27권11호
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• pp.1907-1916
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• 2003

During decades, there has been much progress in understanding of the inelastic behavior of the materials and numerous inelastic constitutive equations have been developed. The complexity of these constitutive equations generally requires a stable and accurate numerical method. To obtain the increment of state variable, its evolution laws are linearized by several approximation methods, such as general midpoint rule(GMR) or general trapezoidal rule(GTR). In this investigation, semi-implicit integration schemes using GTR and GMR were developed and implemented into ABAQUS by means of UMAT subroutine. The comparison of integration schemes was conducted on the simple tension case, and simple shear case and nonproportional loading case. The fully implicit integration(FI) was the most stable but amplified the truncation error when the nonlinearity of state variable is strong. The semi-implicit integration using GTR gave the most accurate results at tension and shear problem. The numerical solutions with refined time increment were always placed between results of GTR and those of FI. GTR integration with adjusting midpoint parameter can be recommended as the best integration method for viscoplastic equation considering nonlinear kinematic hardening.

• 한국정밀공학회지
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• 제16권8호
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• pp.186-192
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• 1999

This paper introduces a study of a method for the forward kinematic analysis, which finds the 6 DOF motions and velocities from the given six cylinder lengths in the Stewart platform. From the viewpoints of kinematics, the solution for the inverse kinematic is easily found by using the vectors of the links which are composed of the joint coordinates in base and plate frames, to act contrary to the serial manipulator, but forward kinematic is difficult because of the nonlinearity and complexity of the Stewart platform dynamic equation with the multi-solutions. Hence we, first in this study, introduce the linear estimator using the Luenberger's observer, and the estimator using the nonlinear measured model for the forward kinematic solutions. But it is difficult to find the parameter of the design for the estimation gain or to select the estimation gain and the constant steady state error exists. So this study suggests the estimator with the estimation gain to be learned by the neural network with the structure of multi-perceptron and the learning method using back propagation and shows the estimation performance using the simulation.

• 한국정밀공학회지
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• 제28권4호
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• pp.391-397
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• 2011

Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered. Based on these clustering centers, least square method is applied for T-S fuzzy linear model parameters. As a result, IPMSM can be modeled as T-S fuzzy model for T-S fuzzy control of them.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.402-403
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• 2014

Damping of multi-span tube with loose supports according to the finite support clearances is investigated through the experimental modal analysis. Loose intermediate support leads to strong nonlinearity in tube dynamics, provides statistical nature, and increases tube damping through impacting and friction at the supports. Fraction of critical damping was estimated by the modal curve fitting to parameter estimation from the measured frequency response functions. Magnitude of random excitation force, which can reproduce the in-situ excitation in operating environment, was maintained as constant value with a fine tolerance during vibration testing. Range of input force was carefully selected to cover from the low magnitude excitation for linearly behaved tube motion to high magnitude of force for nonlinearly-behaved tube motion. Estimated critical damping ratio shows scatters in data and tends to increase as the magnitude of rising force and decrease with upward frequency variation. Larger size of support gap increases multi-span tube damping for high magnitude of excitation.