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Adaptive Neural Network Control for Switched System with Unknown Nonlinear Part by Using Backstepping Approach: SISO Case

  • Fei Long
  • Shumin Fei
  • Zhumu Fu
  • Shiyou Zheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

In this paper, we address, in a backstepping way, stabilization problem for a class of switched nonlinear systems whose subsystem with trigonal structure by using neural network. An adaptive neural network switching control design is given. Backsteppping, domination and adaptive bounding design technique are combined to construct adaptive neural network stabilizer and switching law. Based on common Lyapunov function approach, the stabilization of the resulting closed-loop systems is proved.

Keywords

Adaptive Neural Network Trigonal Structure Adaptive Neural Network Control Adaptive Neural Network Controller Backstepping Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fei Long
    • 1
    • 2
  • Shumin Fei
    • 1
  • Zhumu Fu
    • 1
  • Shiyou Zheng
    • 1
  1. 1.Department of Automatic ControlSoutheast UniversityNanjingP.R. China
  2. 2.School of Information EngineeringGuizhou UniversityGuiyangP.R. China

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