• Wind and Structures
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• v.36 no.3
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• pp.215-220
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• 2023

We study the progressive full-scale wind tunnel tests on a high solidity vertical axis wind turbine (VAWT) for various tip speeds and pitch angles to understand the VAWT shaft system's dynamics using 0-1 Test for chaos. We identify that while varying rotor speed (tip speed) of the turbine, the system's dynamics change from periodic to chaotic through quasiperiodic and strange non-chaotic (SNA) states. The present study is the first experimental evidence for the existence of these states in the VAWT shaft system to the best of our knowledge. Using the asymptotic growth value Kc in 0-1 test, when the turbine operates at the low tip speeds and high pitch angles for low incoming wind speeds, the system behaves periodic (Kc ≈ 0). However, when the incoming wind speed increases further the system's dynamics shift from periodic to chaotic vibrations through quasi-periodic and SNA. This phenomenon is due to the dynamic stalling of blades which induces chaotic vibration in the VAWT shaft system. Further, the singular continuous spectrum method validates the presence of SNA and differentiates the SNA from chaotic vibrations.

• ETRI Journal
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• v.30 no.1
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• pp.170-172
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• 2008

A substitution box (S-box) plays a central role in cryptographic algorithms. In this paper, an efficient method for designing S-boxes based on chaotic maps is proposed. The proposed method is based on the mixing property of piecewise linear chaotic maps. The S-box so constructed has very low differential and linear approximation probabilities. The proposed S-box is more secure against differential and linear cryptanalysis compared to recently proposed chaotic S-boxes.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1843-1850
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• 2015

Controlling nonlinear systems with linear feedback control methods can lead to chaotic behaviors. Order increase in system dynamics due to integral control and control parameter variations in PID controlled nonlinear systems are studied for possible chaos regions in the closed-loop system dynamics. The Lur’e form of the feedback systems are analyzed with Routh’s stability criterion and describing function analysis for chaos prediction. Several novel chaotic systems are generated from second-order nonlinear systems including the simplest continuous-time chaotic system. Analytical and numerical results are provided to verify the existence of the chaotic dynamics.

• Journal of Biomedical Engineering Research
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• v.14 no.4
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• pp.379-386
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• 1993

This paper describes design of a Chaos analyser and its applications to analysis of nonlinear characteristirs of ECG. The proposed system can easily distinguish chaotic system among the various dynamical systems by chaotic quantitative and qualitative analysis and also chaotic characteristics which represents states of nonlinear dynamical system. And we have also proposed new possibilities to recognize abnormal state of ECG signal using the chaotic characteristics.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2852-2854
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• 2005

In this paper, we propose a method to a synchronization of chaotic mobile robots that have unstable limit cycles in a chaos trajectory surface. We assume all obstacles in the chaos trajectory surface have a VDP (Van der Pol) equation with an unstable limit cycle. The proposed methods are assumed that if one of two chaotic mobile robot receives the synchronization command, the other robot also follows the same trajectory during the chaotic robot search on the arbitrary surface.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.324-326
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• 2006

This paper present backstepping control approach for controling chaotic Liu system. The proposed method is a systematic design approach and consists in a recursive procedure that interlaces the choice of a Lyapunov Function. Based on Lyapunov stability theory, control laws are derived. We used the same technique to enable stabilization of chaotic motion to a steady state as well as tracking of any desired trajectory to be achieved in a systematic way. Numerical solution are shown to verify the result.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1234-1239
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• 1993

We study how to design conventional feedback controllers to drive chaotic trajectories of the well-known systems to their equilibrium points or any of their inherent periodic orbits. The well-known chaotic systems are Heon map and Duffing's equation, which are used as illustrative examples. The proposed feedback controller forces the chaotic trajectory to the stable manifold as OGY method does. Simulation results are presented to show the effectiveness of the proposed design method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.453-456
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• 1996

In this paper, the direct adaptive control using neural networks is presented for the control of chaotic nonlinear systems. The direct adaptive control method has an advantage that the additional system identification procedure is not necessary. In order to evaluate the performance of our controller design method, two direct adaptive control methods are applied to a Duffing's equation and a Lorenz equation which are continuous-time chaotic systems. Our simulation results show the effectiveness of the controllers.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.263-266
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• 1998

This paper propose a prefilter type inverse control algorithm using chaotic neural networks. Since the chaotic neural networks show robust characteristics in approximation and adaptive learning for nonlinear dynamic system, the chaotic neural networks are suitable for controlling robotic manipulators. The structure of the proposed prefilter type controller compensate velocity of the PD controller. To estimate the proposed controller, we implemented to the Cartesian space control of three-axis PUMA robot and compared the final result with recurrent neural network(RNN) controller.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2272-2274
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• 1998

This paper presents recognition and classification of high impedance fault(HIF) patterns in the electrical power systems based on chaotic features. Chaotic features are obtained from two dimensional chaos attractors reconstructed from fault current waveform. The RBFN is trained with the two types of HIF data generated by the electromagnetic transient program and measured from actual faults. The RBFN successfully classifies normal and the three types of fault patterns based on the binary chaotic features.