•  
  •  
 

Author Country (or Countries)

China

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.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/080135

Share

COinS