• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.407-410
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• 1996

In this Paper, we propose the feedback method having neural network to control the chaotic signals to periodic signals. This controller has very simple structure, it is immune to small parameter variations, the precise access to system parameters is not required and it is possible to follow ones of its inherent periodic orbits or the desired orbits without error, The controller consist of linear feedback gain and neural network. The learning of neural network is achieved by error-backpropagation algorithm. To prove and analyze the proposed method, we construct a software tool using c-language.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.70-73
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• 1996

Many researchers had considered biological systems as linear systems. In many cases of biological systems, the phenomena that show the regular and periodic dynamics are considered the normal state. However, some clinical experiments reported, in some cases, the periodic signals represented the abnormal state. We assume that signals from human body system are generated from deterministic, intrinsic mechanisms and can be represented a simple equation that show nonlinear dynamics dependent on control parameters. The objective of our study is to model a nonlinear dynamics correctly from the nonlinear time series using the genetic programming method; to find a simple equation of nonlinear dynamics using collected time series and its nonlinear characteristics. We applied genetic programming to model RR interval of ECG that shows chaotic phenomena. We used 4 statistic measures and 2 fractal measures to estimate fitness of each chromosome, and could obtain good solutions of which chaotic features are similar.

• Transactions of the Korean Society of Mechanical Engineers
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• v.7 no.1
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• pp.11-18
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• 1983

For the steady-state solutions of vibratory systems where the dynamics involves nonlinearity and discontinuity, a method of numerical simulation has been normally used. This paper presents a new approach which may overcome some difficulties in the simulation method. This approach is based on the fundamental assumption that the steady-state forced vibration is periodic, so that the problem is formulated as a two-point boundary-value problem and can be solved by Waner's algorithm. This method is demonstrated through the solutions of a linear system, a system with Coulomb friction and an impact pair. It is found that the method gives true solutions well both for linear and nonlinear systems, which convinces us of the usefulness of the method.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.227-236
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• 2005

Multibody system dynamics is based on classical mechanics and its engineering applications originating from mechanisms, gyroscopes, satellites and robots to biomechanics. Multibody system dynamics is characterized by algorithms or formalisms, respectively, ready for computer implementation. As a result simulation and animation are most convenient. Recent developments in multibody dynamics are identified as elastic or flexible systems, respectively, contact and impact problems, and actively controlled systems. Based on the history and recent activities in multibody dynamics, recursive algorithms are introduced and methods for dynamical analysis are presented. Linear and nonlinear engineering systems are analyzed by matrix methods, nonlinear dynamics approaches and simulation techniques. Applications are shown from low frequency vehicles dynamics including comfort and safety requirements to high frequency structural vibrations generating noise and sound, and from controlled limit cycles of mechanisms to periodic nonlinear oscillations of biped walkers. The fields of application are steadily increasing, in particular as multibody dynamics is considered as the basis of mechatronics.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1464-1468
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• 2004

This paper presents a learning controller for repetitive gait control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured according to the walking period through the iterative learning, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of learning control to biped robotic motion is shown via dynamic simulation with 12-DOF biped walking robot.

• Communications of the Korean Mathematical Society
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• v.26 no.2
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• pp.321-338
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• 2011

In this paper, a class of delayed epidemic model with diffusion is investigated. By analyzing the associated characteristic transcendental equation, its linear stability is investigated and Hopf bifurcation is demonstrated. Some explicit formulae determining the stability and the direction of the Hopf bifurcation periodic solutions bifurcating from Hopf bifurcations are obtained by using the normal form theory and center manifold theory. Some numerical simulation are also carried out to support our analytical findings. Finally, biological explanations and main conclusions are given.

• Journal of Mechanical Science and Technology
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• v.16 no.6
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• pp.819-828
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• 2002

An analytical method is presented for evaluation of the steady state periodic behavior of nonlinear systems. This method is based on the substructure synthesis formulation and a MS (multiple scales) procedure, which is applied to the analysis of nonlinear responses. The proposed procedure reduces the size of large degrees-of-freedom problem in solving nonlinear equations. Feasibility and advantages of the proposed method are illustrated with the nonlinear rotating machine system as an example of large mechanical structure systems. In addition, its efficiency for nonlinear response prediction will be shown by comparison of other conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.152-158
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• 2003

A machine-vision guided inspection system with go-no gauges for inspecting eggcrate assemblies in steam generators is considered. To locate the gauge at the right place, periodic corrective actions for its position and traveling direction are required. We present a machine vision algorithm for determining inserting position and traveling direction of the go-no gauge. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid-height adjustment, intersection point estimation between two intersecting grids, and adjustment of position and traveling direction of the gauge. The intersection point estimation is performed by using linear regression with a constraint. A test with a real eggcrate specimen shows the feasibility of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.598-603
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• 2005

In this study, an adaptive control scheme with a pre-specified $H_{\infty}$ property is proposed for the tracking control of linear induction motor (LIM) drive system. Under the influence of uncertainties and external disturbances, by using nonlinear decoupling and parameter tuner, the robust performance control problem is formulated as a nonlinear $H_{\infty}$ problem and solved by a quadratic storage function. This new design method is able to track the step and several periodic commands with improved performance in face of parameter perturbations and external disturbances. Simulation and experimental results are provided to demonstrate the effectiveness of the proposed adaptive $H_{\infty}$ controller.

• Bulletin of the Korean Chemical Society
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• v.24 no.2
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• pp.178-182
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• 2003

The stress and the heat-flux auto-correlation functions in the Green-Kubo formulas for shear viscosity and thermal conductivity have non-decaying long-time tails. This problem can be overcome by improving the statistical accuracy by N (number of particles) times, considering the stress and the heat-flux of the system as properties of each particle. The mean square stress and the heat-flux displacements in the Einstein formulas for shear viscosity and thermal conductivity are non linear functions of time since the quantities in the mean square stress and the heat-flux displacements are not continuous under periodic boundary conditions. An alternative to these quantities is to integrate the stress and the heat-flux with respect to time, but the resulting mean square stress and heat-flux displacements are still not linear versus time. This problem can be also overcome by improving the statistical accuracy. The results for transport coefficients of liquid argon obtained are discussed.