• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.42-51
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• 1999

This research deals with the non-linearities associated with impact and sliding for the rocking behavior of rigid block subjected to two dimensional excitation of horizontal and vertical direction. The non-linearities examined of impact between block and base: The transition of two governing rocking equations, the abrupt reduction in kinetic energy associated with impact. In this study, the rocking vibration system of two types are considered for several friction condition. One is the undamped rocking vibration system, disregarding energy dissipation at impact and the other is the damped rocking system, including energy dissipation at impact. The response analysis by non-dimensional rocking equation is carried out for the change of excitation amplitude. The chaos responses were discovered in the wide response region, particularly, in the case of high vertical excitation and their chaos characteristics are examined by Poincare map, power spectra and Lyapunov Exponent. The complex behavior of chaos response, in the phase space, were illustrated by Poincare map. Therefore, Poincare map will be a significant material in order to understand chaos of rocking system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.495-508
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• 1995

The self-excited vibrations of airfoil is related to the classical flutter problems, and it has been studied as a system with linear stiffness and small damping. However, since the actual aircraft wing and the many mechanical elements of airfoil type have various design variables and parameters, some of these could have strong nonlinearities, and the nonlinearities could be unexpectedly strong as the parameters vary. This abrupt chaotic behavior undergoes ordered routes, and the behaviors after these routes are uncontrollable and unexpectable since it is extremely sensitive to initial conditions. In order to study the chaotic behavior of the system, three parameters are considered, i.e., free-stream velocity, elastic distance and zero-lift angle. If the chaotic parameter region can be identified from the mathematically modeled nonlinear differential equation system, the designs which avoid chaotic regions could be suggested. In this study, by using recently developed dynamically system methods, and chaotic regions on the parameter plane will be found and the safe design variables will be suggested.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1139-1144
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• 2012

The ration of payload to weight of industrial robot amounts form 1:10 to 1:30. Compared with man who have a ration of 3:1, it is very low. One of the goals for the next generation of robots will be a ration. This might be possible only by developing lightweight robots. When two-link flexible arm is rotated about an joint axis, transverse vibration may occur. In this paper, vibration dynamics of flexible arm is modeled by using Bernoulli-Euler beam theory and Lagrange equation. Using the fact that matrix $\dot{D}-2C$ is skew symmetric, new controllers which have a simplified structure with less computational burden is proposed by using Lyapunov stability theory. We propose deterministic and adaptive control laws for two link flexible arm, and the validity of the proposed control scheme is shown in computer simulation for two-link flexible arm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.45-53
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• 2000

This paper presents an analysis of the dynamical behavor in the chaotic neuron fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation models for the sigmoid output function and chaos generative block of the chaotic neuron are extracted from the measurement data. Then the dynamical responses of the chaotic neuron such as biurcation diagram, frequency responses, Lyapunov exponent, and average firing rate are calculated with numerical analysis. In addition, we construct the chaotic neural networks which are composed of two chaotic neurons with four synapses and obtain bifurcation diagram according to synaptic weight variation. And results of experiments in the single chaotic neuron and chaotic neural networks by two neurons with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.