|Table of Contents|

Interval type II fuzzy neural network control based robust adaptivefor the synchronization of uncertain chaotic systems(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2019年04期
Page:
432-438
Research Field:
Publishing date:

Info

Title:
Interval type II fuzzy neural network control based robust adaptivefor the synchronization of uncertain chaotic systems
Author(s):
Li HongmeiGao YuanChen Xiangjian
School of Computer,Jiangsu University of Science and Technology,Zhenjiang 212003,China
Keywords:
uncertain chaotic systems chaos synchronization adaptive control interval type Ⅱ fuzzy neural network Lyapunov stability
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2019.43.04.008
Abstract:
This paper proposes a robust adaptive interval type II fuzzy neural network control(RAITIIFNNC)to address the problem of controlled synchronization of a class of uncertain chaotic systems. The proposed RAITIIFNNC system is comprised of an interval type II fuzzy neural network identifier and a robust controller. The identifier is utilized for online estimation of the compound uncertainties. The robust controller is used to attenuate the effects of the approximation error so that the perfect tracking and synchronization of chaotic systems are achieved. All the parameter learning algorithms are derived based on Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. From the simulation example,to synchronize two Lorenz chaotic systems,the effectiveness of the proposed method has been verified.

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Last Update: 2019-09-30