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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 8 > No. 1

 
   

Direct Adaptive H∞ Control for a Class of Nonlinear Systems based on LS-SVM

PP: 287-292
Author(s)
Dan-Dan Zhao, Chun-Li Xie, Pei-Chang Wang,
Abstract
A scheme of direct adaptive H∞ control based on least squares support vector machines (LS-SVM) is proposed for a class of nonlinear uncertain systems. In this method, LS-SVM is employed to construct the adaptive controller, and an on-line learning rule for the weighting vector and bias is derived. A parameter selection method based on the genetic algorithm (GA) is given for LS-SVM regression with Gauss kernel. H∞ control is used to attenuate the effect on the tracking error caused by LS-SVM approximation errors and external disturbances. Lyapunov theory is used to prove the uniformly ultimately bounded stability of the close-loop system. The simulation result shows the effectiveness and feasibility of the proposed method.

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