Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

Qiang Chen*, Xuemei Ren, Jing Na

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

10 Citations (Scopus)

Abstract

In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1080-1088
Number of pages9
JournalChaos, Solitons and Fractals
Volume44
Issue number12
DOIs
Publication statusPublished - 1 Dec 2011

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