Men of chaos,

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Saints of chaos

--Harbingers of change.-- Martin Luther.-- Galileo Galilei.--Ludwig van Beethoven.-- James Watt.-- Thomas Hobbes.-- The new unity.

Evolution of life from chaos to Christ; Easter offering, by Conrad Siem.

Mode of access: Internet.

Analysis of chaotic instabilities in a rotating body with internal energy dissipation

Melnikov's method is used to analytically predict the onset of chaotic instability in a rotating body with internal energy dissipation. The model has been found to exhibit chaotic instability when a harmonic disturbance torque is applied to the system for a range of forcing amplitude and frequency. Such a model may be considered to be representative of the dynamical behavior of a number of physical systems such as a spinning spacecraft. In spacecraft, disturbance torques may arise under malfunction of the control system, from an unbalanced rotor, from vibrations in appendages or from orbital variations. Chaotic instabilities arising from such disturbances could introduce uncertainties and irregularities into the motion of the multibody system and consequently could have disastrous effects on its intended operation. A comprehensive stability analysis is performed and regions of nonlinear behavior are identified. Subsequently, the closed form analytical solution for the unperturbed system is obtained in order to identify homoclinic orbits. Melnikov's method is then applied on the system once transformed into Hamiltonian form. The resulting analytical criterion for the onset of chaotic instability is obtained in terms of critical system parameters. The sufficient criterion is shown to be a useful predictor of the phenomenon via comparisons with numerical results. Finally, for the purposes of providing a complete, self-contained investigation of this fundamental system, the control of chaotic instability is demonstated using Lyapunov's method.

Suppressing chaos via Lyapunov-Krasovskii's method

An algorithm for suppressing the chaotic oscillations in non-linear dynamical systems with singular Jacobian matrices is developed using a linear feedback control law based upon the Lyapunov-Krasovskii (LK) method. It appears that the LK method can serve effectively as a generalised method for the suppression of chaotic oscillations for a wide range of systems. Based on this method, the resulting conditions for undisturbed motions to be locally or globally stable are sufficient and conservative. The generalized Lorenz system and disturbed gyrostat equations are exemplified for the validation of the proposed feedback control rule. (c) 2005 Elsevier Ltd. All rights reserved.

Chaos Theory as an Approach to Understanding MICE in Time of Crisis

MICE (meetings, incentives, conventions, and exhibitions), has generated high foreign exchange revenue for the economy worldwide. In Thailand, MICE tourists are recognized as ‘quality’ visitors, mainly because of their high-spending potential. Having said that, Thailand’s MICE sector has been influenced by a number of crises following September 11, 2001. Consequently, professionals in the MICE sector must be prepared to deal with such complex phenomena of crisis that might happen in the future. While a number of researches have examined the complexity of crises in the tourism context, there has been little focus on such issues in the MICE sector. As chaos theory provides a particularly good model for crisis situations, it is the aim of this paper to propose a chaos theory-based approach to the understanding of complex and chaotic system of the MICE sector in time of crisis.

Control of spatiotemporal chaos in catalytic CO oxidation by laser-induced pacemakers

Control of spatiotemporal chaos is achieved in the catalytic oxidation of CO on Pt(110) by localized modification of the kinetic properties of the surface chemical reaction. In the experiment, a small temperature heterogeneity is created on the surface by a focused laser beam. This heterogeneity constitutes a pacemaker and starts to emit target waves. These waves slowly entrain the medium and suppress the spatiotemporal chaos that is present in the absence of control. We compare this experimental result with a numerical study of the Krischer-Eiswirth-Ertl model for CO oxidation on Pt(110). We confirm the experimental findings and identify regimes where complete and partial controls are possible.

Suppression of spatiotemporal chaos in the oscillatory CO oxidation on Pt(110) by focused laser light

Chemical turbulence in the oscillatory catalytic CO oxidation on Pt(110) is suppressed by means of focused laser light. The laser locally heats the platinum surface which leads to a local increase of the oscillation frequency, and to the formation of a pacemaker which emits target waves. These waves slowly entrain the medium and suppress the spatiotemporal chaos present in the absence of laser light. Our experimental results are confirmed by a detailed numerical analysis of one- and two-dimensional media using the Krischer-Eiswirth-Ertl model for CO oxidation on Pt110. Different control regimes are identified and the dispersion relation of the system is determined using the pacemaker as an externally tunable wave source.

Quantifying the complexity of chaos in multibasin multidimensional dynamics of molecular systems

The simulated classical dynamics of a small molecule exhibiting self-organizing behavior via a fast transition between two states is analyzed by calculation of the statistical complexity of the system. It is shown that the complexity of molecular descriptors such as atom coordinates and dihedral angles have different values before and after the transition. This provides a new tool to identify metastable states during molecular self-organization. The highly concerted collective motion of the molecule is revealed. Low-dimensional subspaces dynamics is found sensitive to the processes in the whole, high-dimensional phase space of the system. © 2004 Wiley Periodicals, Inc.

Neural Control of Chaos and Aplications

Signal processing is an important topic in technological research today. In the areas of nonlinear dynamics search, the endeavor to control or order chaos is an issue that has received increasing attention over the last few years. Increasing interest in neural networks composed of simple processing elements (neurons) has led to widespread use of such networks to control dynamic systems learning. This paper presents backpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodic orbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading to more efficient system control. The procedure can be applied to every point of the basin, no matter how far away from the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using a backpropagation neural network as a filter to separate and control both signals at the same time. The neural network provides more effective control, overcoming the problems that arise with control feedback methods. Control is more effective because it can be applied to the system at any point, even if it is moving away from the target state, which prevents waiting times. Also control can be applied even if there is little information about the system and remains stable longer even in the presence of random dynamic noise.