• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.3
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• pp.433-441
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• 2001

Natural convection of a fluid with intermediate Prand시 number of Pr=0.2 in a horizontal annulus is considered, and the bifurcation phenomena and chaotic flows are numerically investigated. The unsteady two-dimensional streamfunction-vorticity equation is solved with finite difference method. The steady downward flow with two counter-rotating eddies bifurcates to a simple periodic flow with a fundamental frequency. And afterwards, second Hopf bifurcation occurs, and a quasi-periodic flow with two incommensurable frequencies appears. However, a new time-periodic flow is established after experiencing quasi-periodic states. As Rayleigh number is increased further, the chaotic flow regime is reached after a sequence of successive Hopf bifurcation to quasi-periodic and chaotic flow regimes. A scenario similar to the Ruelle-Takens-Newhouse scenario of the onset of chaos is observed.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.244-249
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• 1998

In this paper, the hybrid state space self-tuning control technique Is studied within the framework of fuzzy systems and dual-rate sampling control theory. We show that fuzzy modeling techniques can be used to formulate chaotic dynamical systems. Then, we develop the hybrid state space self-tuning fuzzy control techniques with dual-rate sampling for digital control of chaotic systems. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the continuous-time optimal state feedback gains, the constructed discrete-time fuzzy system is converted into a continuous-time system. The developed optimal continuous-time control law is then convened into an equivalent slow-rate digital control law using the proposed digital redesign method. The proposed technique enables us to systematically and effective]y carry out framework for modeling and control of chaotic systems. The proposed method has been successfully applied for controlling the chaotic trajectories of Chua's circuit.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.12-21
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• 1998

A chaotic spread spectrum communication system using a polar quarternary method is designed and implemented. Four different chaotic signals in the relation of multiplication each other are generated through the use of a coupled synchronization method in the transmitter which is composed of four Chua's circuits. Information is retrieved at the receiver which is connected to the transmitter through the use of a drive synchronization method. Since spread spectrum of information signal is spread by chaotic signal, the configuration of the system is simpler than that of any other conventional system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.183-186
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• 2002

In this paper, a predictive control method using wavelet neural network for chaotic nonlinear systems is presented. In our method, we use the adjusting method of the parameter for the training a wavelet neural network. The control signals are directly obtained by minimizing the difference between a reference signal and the output of a wavelet neural network. To verify the efficiency of our method, we apply it to the Duffing and the Henon system, which are a representative continuous and discrete time chaotic nonlinear system respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.478-485
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• 1999

The purpose of this paper was the determination of the relationship between the chaotic charateristics and various levels of brain activities. Assuming that EEG(eletroencephalogram), which is generated by a nonlinear electiecal behavior of billions of neurons in the brain, has chaotic characteristics, it was confirmed by frequency spectrum analysis, log frequency spectrum analysis, correlation dimension analysis and Lyapunov exponents analysis. Chaotic characteristics are related to the degree of brain activity. The slope of log frequency spectrum increased and the correlation dimension decreased with respect to the brain activities, while the lagrest Lyapunov exponent has some rough correlation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.602-611
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• 1996

In this paper, radial basis function networks with two hidden layers, which employ the K-means clustering method and the hierarchical training, are proposed for improving the short-term predictability of chaotic time series. Furthermore the recursive training method of radial basis function network using the recursive modified Gram-Schmidt algorithm is proposed for the purpose. In addition, the radial basis function networks trained by the proposed training methods are compared with the X.D. He A Lapedes's model and the radial basis function network by nonrecursive training method. Through this comparison, an improved radial basis function network for predicting chaotic time series is presented. (author). 17 refs., 8 figs., 3 tabs.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.184-191
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• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2187-2189
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• 2003

This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of chaotic systems. The conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on a direct adaptive control method is proposed to control chaotic systems whose mathematical models are not available. The gradient-descent method is used for training a wavelet neural network controller. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic system.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.258-262
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• 1996

The physiological systems have nonlinear complex phenomena. Expecially, the flow of capillary blood vessel has a nonlinear dynamic system. Thus, this study analyzes nonlinear characteristics of the flow of capillary blood vessel in physiological systems using chaotic tools(phase space reconstruction, correlation dimension, largest lyapunov exponent). Experimental data have been acquired from examining 10 rabbits. The results of chaotic analysis showed a decreasing largest lyapunov exponent and correlation dimension according to increasement glocose index. And we also know the chaotic behavior.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.197-204
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• 2005

In this paper, we propose a method to an obstacle avoidance of chaotic robots that have unstable limit cycles in a chaos trajectory surface in the ubiquitous environment. We assume all obstacles in the chaos trajectory surface have a Van der Pol equation with an unstable limit cycle. We also show computer simulation results of Chua's equation, Lorenz equation, Hamilton and Hyper-chaos equation trajectories with one or more Van der Pol as an obstacles. We proposed and verified the results of the method to make the embedding chaotic mobile robot to avoid with the chaotic trajectory in any plane.