Controlling Chaos | ScienceGate

In this study, we propose a novel fractional-order Jerk system. Experiments show that, under some suitable parameters, the fractional-order Jerk system displays a chaotic phenomenon. In order to suppress the chaotic behavior of the fractional-order Jerk system, we design two control strategies. Firstly, we design an appropriate time delay feedback controller to suppress the chaos of the fractional-order Jerk system. The delay-independent stability and bifurcation conditions are established. Secondly, we design a suitable mixed controller, which includes a time delay feedback controller and a fractional-order PDσ controller, to eliminate the chaos of the fractional-order Jerk system. The sufficient condition ensuring the stability and the creation of Hopf bifurcation for the fractional-order controlled Jerk system is derived. Finally, computer simulations are executed to verify the feasibility of the designed controllers. The derived results of this study are absolutely new and possess potential application value in controlling chaos in physics. Moreover, the research approach also enriches the chaos control theory of fractional-order dynamical system.

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Controlling Chaos in a Food Chain Model through Threshold Harvesting

Fisheries and Aquaculture Journal ◽

10.4172/2150-3508.1000142 ◽

2015 ◽

Vol 06 (04) ◽

Cited By ~ 1

Author(s):

Mohammad Ali Khan ◽

Joydev Ghosh

Keyword(s):

Food Chain ◽

Chain Model ◽

Controlling Chaos ◽

Food Chain Model

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Controlling chaos of a dynamical system with discontinuous vector field

Physica D Nonlinear Phenomena ◽

10.1016/s0167-2789(97)00023-7 ◽

1997 ◽

Vol 106 (1-2) ◽

pp. 1-8 ◽

Cited By ~ 16

Author(s):

Haiyan Hu

Keyword(s):

Dynamical System ◽

Vector Field ◽

Controlling Chaos

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Controlling Chaos with Artificial Neural Network: Numerical Studies and Experiments

The Journal of Physical Chemistry A ◽

10.1021/jp001316w ◽

2000 ◽

Vol 104 (34) ◽

pp. 8033-8037 ◽

Cited By ~ 9

Author(s):

István Z. Kiss ◽

Vilmos Gáspár

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Controlling Chaos ◽

Numerical Studies ◽

Artificial Neural

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Experimental Techniques for Controlling Chaos in Lasers

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127498001467 ◽

1998 ◽

Vol 08 (09) ◽

pp. 1759-1768 ◽

Cited By ~ 3

Author(s):

R. Meucci ◽

A. Labate ◽

M. Ciofini

Keyword(s):

Power Spectrum ◽

Chaotic Dynamics ◽

Feedback Loop ◽

Control Parameter ◽

Experimental Techniques ◽

Controlling Chaos ◽

Sinusoidal Modulation ◽

Control Schemes ◽

Frequency Components

This paper presents two control schemes for the chaotic dynamics of CO 2 laser with feedback which can be applied after the recognition of a leading frequency of the motion in the power spectrum. The first one is realized by means of a selective feedback loop which rejects all the frequency components except that of the leading cycle to be stabilized. The second one consists in a resonant sinusoidal modulation of the control parameter.

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