4.7 Article

A recursive delayed output-feedback control to stabilize chaotic systems using linear-in-parameter neural networks

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ELSEVIER
DOI: 10.1016/j.cnsns.2010.04.015

Keywords

Chaotic systems; Delayed feedback control; Intelligent control; Neural networks

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In this paper, a recursive delayed output-feedback control strategy is considered for stabilizing unstable periodic orbit of unknown nonlinear chaotic systems. An unknown nonlinearity is directly estimated by a linear-in-parameter neural network which is then used in an observer structure. An on-line modified back propagation algorithm with e-modification is used to update the weights of the network. The globally uniformly ultimately boundedness of overall closed-loop system response is analytically ensured using Razumikhin lemma. To verify the effectiveness of the proposed observer-based controller, a set of simulations is performed on a Rossler system in comparison with several previous methods. (C) 2010 Elsevier B.V. All rights reserved.

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