Neural Network Control for a Class of Stochastic Nonlinear Switched System Based on Backstepping

  • Authors:
  • Sheng Zhang;Fei Long

  • Affiliations:
  • College of Computer Science and Information Engineering, Guizhou University,Guiyang, Guizhou, P. R. China 550025;College of Computer Science and Information Engineering, Guizhou University,Guiyang, Guizhou, P. R. China 550025

  • Venue:
  • ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
  • Year:
  • 2009

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Abstract

In this paper, we deal with the switched stabilization problem for a class of stochastic switched nonlinear systems based on RBF neural network and backstepping approach. By using the combination design technique of backstepping and neural network, an adaptive neural network switching controller is designed for the switched stabilization of stochastic switched nonlinear system with trigonal structure. It is shown that, under Stochastic Lasalle Theorem, the resulting closed-loop system is proved to be globally asymptotically stable in probability.