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中国物理学会期刊

基于最小二乘支持向量机的混沌控制

CSTR: 32037.14.aps.54.4019

Chaos control based on least square support vector machines

CSTR: 32037.14.aps.54.4019
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  • 利用支持向量机良好的非线性函数逼近和泛化能力,提出基于最小二乘支持向量机非线性补偿的混沌控制新方法.应用最小二乘支持向量机离线辨识混沌系统的非线性部分,并用辨识模型补偿系统的非线性,同时应用线性状态反馈控制混沌系统.对三种典型连续混沌系统的仿真研究表明,提出的控制方法可以有效的控制混沌系统到达设定的目标状态,并且由线性状态反馈控制器构成的闭环系统稳定.

     

    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.

     

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