Open AccessChaos control based on least square support vector machines
Author(s) -
Ran Liu,
Ding Liu,
Hang Ren
Publication year - 2005
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.54.4019
Subject(s) - chaotic , control theory (sociology) , nonlinear system , support vector machine , generalization , computer science , controller (irrigation) , chaos (operating system) , identification (biology) , square (algebra) , control (management) , mathematics , artificial intelligence , physics , mathematical analysis , computer security , geometry , quantum mechanics , agronomy , biology , botany
A new chaos control method based on Least-Square Support Vector Machines (LS-SVM) is proposed which has the excellent nonlinearity approximation ability and b etter generalization capability. Many chaotic systems can be composed into a sum of a linear and a nonlinear parts. LS-SVM has been applied in off-line identification of nonlinear part in continuous chaos system, and the identification mode l has been joined in system to compensate nonlinearity. Subsequently a linear st ate feedback controller has been developed to drive chaotic system to desirable points. It is proven by simulations for three representative continuous chaotic systems that the proposed method is effective to control the chaotic system and closed-loop system with state feedback, and the LS-SVM approximator is stable.