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.
Digital Object Identifier (DOI)
Zhao, Dan-Dan; Xie, Chun-Li; and Wang, Pei-Chang
"Direct Adaptive H∞ Control for a Class of Nonlinear Systems based on LS-SVM,"
Applied Mathematics & Information Sciences: Vol. 08:
1, Article 35.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss1/35