Finite-Time Synchronizing Control for Chaotic Neural Networks

Abstract and Applied Analysis

Research Article

Jing Wang¹  Qiang Guo¹  Chao Zhang¹ 

[1] National Engineering Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing 100083, China, ustb.edu.cn

Others  :  1320962
DOI  :  10.1155/2014/938612

 received in 2014-04-11, accepted in 2014-06-04,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

CC BY   
Copyright © 2014 Chao Zhang et al. 2014

【 图 表 】

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