• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.2
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• pp.291-301
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• 1999

A method for the synthesis of one-dimensional nonlinear distribution function is presented for the desired inverse scattering pattern. This method is based on the inverse transform of the solution of the Riccati equation derived from one-dimensional inverse scattering problem. Since the solution is analogous to the array factor or normalized space factor in collinear array antenna, the synthesis method for field pattern is applied for the construction of the involved line-source nonlinear distribution function. The suggested method is carried out under the optimization process, and is numerically verified by synthesizing the dispersive transmission line profile within the specified frequency band and control of scattered field on resistive strip.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.1003-1009
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• 1995

In This Paper, Linearization problem is discussed to reduce distortion of a nonlinear system based on Schetzen's pth-orfer inverse theorem. We propose a nonlinear adaptive prefiltering algorithm which can reduse nonlinear distortion up to pth order by tandemly connecting a pth-order Volterra filter before the nonlinear system under the consideration and by adjusting the filter coefficients adaptively. The feasibility of applying the proposed algorithm to a nonlinear system is conformed via computer simulation by observing significant reduction of total nonlinear distortion for the case of random input and sinusoidal input excitation.

• Advances in aircraft and spacecraft science
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• v.4 no.4
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• pp.437-448
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• 2017

The problem of flow through the vent is formulated as an unsteady, nonlinear, ordinary differential equation and solved using Runge-Kutta method to obtain pressure inside payload faring. An inverse problem for prediction of the discharge coefficient is presented employing measured internal pressure of the payload fairing during the ascent phase of a satellite launch vehicle. A controlled random search method is used to estimate the discharge coefficient from the measured transient pressure history during the ascent period of the launch vehicle. The algorithm predicts the discharge coefficient stepwise with function of Mach number. The estimated values of the discharge coefficients are in good agreement with differential pressure measured during the flight of typical satellite launch vehicle.

• Journal of KSNVE
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• v.10 no.5
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• pp.800-805
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• 2000

To determine the modal matrix and modal frequency of engine mount system, we most solve so-called eigen-value problem. However eigen-value problem of engine mount system with hydraulic mount can not be solved by general eigne-analysis algorithm because the properties of hydraulic mount vary with frequency. so in this paper the method for modal analysis of rigid body motions of an engine supported by hydraulic mount is proposed. Natural frequencies and mode shapes of this nonlinear system are obtained by using complex exponential method and Laplace transformation method. In time domain, impulse response functions are calculated by (two-sided) discrete inverse Fourier Transformation of forced frequency response functions achieved by Laplace transformation of the differential equation of motion. Considering the fact that frequency response functions synthesized by modal parameters form proposed method are in good agreement with original FRFs, it is proved that the proposed method is very efficient and useful for the analysis of eigne-value problem of hydraulic engine mount system.

• Korean Journal of Mathematics
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• v.17 no.2
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• pp.219-231
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• 2009

We show the existence of at least four solutions for the perturbed parabolic equation with Dirichlet boundary condition and periodic condition when the nonlinear part cross two eigenvalues of the eigenvalue problem of the Laplace operator with boundary condition. We obtain this result by using the Leray-Schauder degree theory, the finite dimensional reduction method and the geometry of the mapping. The main point is that we restrict ourselves to the real Hilbert space instead of the complex space.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.9
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• pp.985-996
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• 1990

An inverse kinematic solution of a robot manipulator using multilayer perceptrons is proposed. Neural networks allow the solution of some complex nonlinear equations such as the inverse kinematics of a robot manipulator without the need for its model. However, the back-propagation (BP) learning rule for multilayer perceptrons has the major limitation of being too slow in learning to be practical. In this paper, a new algorithm named Dynamically Reconfiguring BP is proposed to improve its learning speed. It uses a modified version of Kohonen's Self-Organizing Feature Map (SOFM) to partition the input space and for each input point, select a subset of the hidden processing elements or neurons. A subset of the original network results from these selected neuron which learns the desired mapping for this small input region. It is this selective property that accelerates convergence as well as enhances resolution. This network was used to learn the parity function and further, to solve the inverse kinematic problem of a robot manipulator. The results demonstrate faster learning than the BP network.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.539-551
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• 2021

With the continuous increase of computational capacity, more and more complex nonlinear elastoplastic constitutive models were developed to study the mechanical behavior of elastoplastic materials. These constitutive models generally contain a large amount of physical and phenomenological parameters, which often require a large amount of computational costs to determine. In this paper, an inverse parameter determination method is proposed to identify the constitutive parameters of elastoplastic materials, with the consideration of both strain rate effect and temperature effect. To carry out an efficient design, a hybrid optimization algorithm that combines the genetic algorithm and the Nelder-Mead simplex algorithm is proposed and developed. The proposed inverse method was employed to determine the parameters for an elasto-viscoplastic constitutive model and Johnson-cook model, which demonstrates the capability of this method in considering strain rate and temperature effect, simultaneously. This hybrid optimization algorithm shows a better accuracy and efficiency than using a single algorithm. Finally, the predictability analysis using partial experimental data is completed to further demonstrate the feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.73-80
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• 2004

In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theorr is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.