Adaptive neural dynamic surface control of nonlinear time-delay systems with model uncertainties

Sung Jin Yoo, Jin Bae Park, Yoon Ho Choi

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

18 Citations (Scopus)

Abstract

In this paper, the adaptive dynamic surface control (DSC) method is presented for a class of uncertain nonlinear systems with unknown time delays in strict-feedback form. Using the DSC technique, the problem of "explosion of complexity" of the traditional backstepping algorithm can be eliminated and the uncertainties of the unknown time delays are overcome by using appropriate Lyapunov-Krasovskii functionals. Self recurrent wavelet neural networks are employed to observe the arbitrary model uncertainties and the external disturbance online. In addition, it is proved that all the signals in the closed-loop system are semi-globally uniformly bounded. Finally, a simulation result is utilized to illustrate the effectiveness of the proposed control system.

Original languageEnglish
Title of host publicationProceedings of the 2006 American Control Conference
Pages3140-3145
Number of pages6
Publication statusPublished - 2006 Dec 1
Event2006 American Control Conference - Minneapolis, MN, United States
Duration: 2006 Jun 142006 Jun 16

Publication series

NameProceedings of the American Control Conference
Volume2006
ISSN (Print)0743-1619

Other

Other2006 American Control Conference
CountryUnited States
CityMinneapolis, MN
Period06/6/1406/6/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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  • Cite this

    Yoo, S. J., Park, J. B., & Choi, Y. H. (2006). Adaptive neural dynamic surface control of nonlinear time-delay systems with model uncertainties. In Proceedings of the 2006 American Control Conference (pp. 3140-3145). [1657200] (Proceedings of the American Control Conference; Vol. 2006).