|
|
 |
| |
|
|
|
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. |
|
|
|
|
|
|
|
