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Direct Adaptive Neural Dynamic Surface Control of Uncertain Nonlinear Systems with Input Saturation

  • Junfang Li
  • Tieshan Li
  • Yongming Li
  • Ning Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

In this paper, we present a new scheme to design direct adaptive neural network controller for uncertain nonlinear systems in the presence of input saturation. By incorporating dynamic surface control (DSC) technique into a neural network based adaptive control design framework, the control design is achieved. With this technique, the problem of “explosion of complexity” inherent in the conventional backstepping method is avoided, and the controller singularity problem is removed, and the effect of input saturation constrains is considered. In addition, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, simulation studies are given to demonstrate the effectiveness of the proposed scheme.

Keywords

Adaptive control dynamic surface control input saturation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Junfang Li
    • 1
  • Tieshan Li
    • 1
  • Yongming Li
    • 1
  • Ning Wang
    • 1
  1. 1.Navigation CollegeDalian Maritime UniversityDalianP.R. China

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