Adaptive nn control for a class of non-affine nonlinear systems with unknown control gain

Beibei Ren, Shuzhi Sam Ge, Tong Heng Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, adaptive neural network (NN) control is presented for a class of non-affine nonlinear systems with unknown control gain. Using the Mean Value Theorem and backstepping method, we propose a constructive approach for adaptive NN control design. The Nussbaum function is used to relax the requirement on control direction. The semi-global uniformly ultimately boundedness (SGUUB) of the closed-loop system is achieved. In addition, the simulation study results are given to demonstrate the effectiveness of the proposed control.

Original languageEnglish
Title of host publication3rd IFAC Workshop on Advanced Fuzzy and Neural Control, AFNC 2007
PublisherIFAC Secretariat
Pages163-168
Number of pages6
EditionPART 1
ISBN (Print)9783902661333
DOIs
StatePublished - 2007

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume3
ISSN (Print)1474-6670

Keywords

  • Adaptive
  • Neural networks
  • Non-affine
  • Nussbaum function

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    Ren, B., Ge, S. S., & Lee, T. H. (2007). Adaptive nn control for a class of non-affine nonlinear systems with unknown control gain. In 3rd IFAC Workshop on Advanced Fuzzy and Neural Control, AFNC 2007 (PART 1 ed., pp. 163-168). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 3, No. PART 1). IFAC Secretariat. https://doi.org/10.3182/20071029-2-fr-4913.00028