Abstract and Applied Analysis

Finite-Time Synchronizing Control for Chaotic Neural Networks

Chao Zhang, Qiang Guo, and Jing Wang

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Abstract

This paper addresses the finite-time synchronizing problem for a class of chaotic neural networks. In a real communication network, parameters of the master system may be time-varying and the system may be perturbed by external disturbances. A simple high-gain observer is designed to track all the nonlinearities, unknown system functions, and disturbances. Then, a dynamic active compensatory controller is proposed and by using the singular perturbation theory, the control method can guarantee the finite-time stability of the error system between the master system and the slave system. Finally, two illustrative examples are provided to show the effectiveness and applicability of the proposed scheme.

Article information

Source
Abstr. Appl. Anal., Volume 2014, Special Issue (2014), Article ID 938612, 9 pages.

Dates
First available in Project Euclid: 2 October 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1412278511

Digital Object Identifier
doi:10.1155/2014/938612

Mathematical Reviews number (MathSciNet)
MR3226241

Zentralblatt MATH identifier
07023352

Citation

Zhang, Chao; Guo, Qiang; Wang, Jing. Finite-Time Synchronizing Control for Chaotic Neural Networks. Abstr. Appl. Anal. 2014, Special Issue (2014), Article ID 938612, 9 pages. doi:10.1155/2014/938612. https://projecteuclid.org/euclid.aaa/1412278511


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