Fractional order chaotic system control based on feedback and multiple least square support vector machines
Wang Rui1, Yang Hong2
(1)School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China; (2)School of Physics and Electronic Engineering, Guangzhou University, Guangzhou 510006, China
Abstract According to the stability of fractional order linear systems theory, the system is decomposed into stable linear parts and the corresponding nonlinear parts. The active controller is designed to compensate the nonlinear parts, and the fractional order chaotic system is suppressed to an equilibrium point. In order to improve the compensation ability of active controller, a multiple least square support vector machine (M-LS-SVM) regression model is presented based on feedback. The subtractive clustering is adopted to divide the input space into several sub-spaces, and sub-models are built by a LS-SVM in each sub-space. In order to minimize the severe correlation among sub-models and to improve the accuracy and the robustness of the model, the sub-models are combined by principal component regression (PCR).The experiment result shows that by using the method the compensation accuracy and the system response indices can be improved.
Yang Hong,Wang Rui. Fractional order chaotic system control based on feedback and multiple least square support vector machines. Acta Phys. Sin., 2011, 60(7): 070508.
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2011, Vol. 60 
