Adaptive neural control of SISO time-delay nonlinear systems with unknown hysteresis input

Tong Heng Lee, Beibei Ren, Shuzhi Sam Ge

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

Abstract

In this paper, adaptive variable structure neural control is investigated for a class of SISO nonlinear systems in a Brunovsky form with state time-varying delays and unknown hysteresis input. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The effect of the unknown hysteresis with the Prandtl-Ishlinskii model is mitigated using the proposed adaptive control. By utilizing the integral-type Lyapunov function, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the approach.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Edition1 PART 1
DOIs
StatePublished - 2008
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: Jul 6 2008Jul 11 2008

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Conference

Conference17th World Congress, International Federation of Automatic Control, IFAC
CountryKorea, Republic of
CitySeoul
Period07/6/0807/11/08

Keywords

  • Adaptive control
  • Lyapunov methods
  • Nonlinear system control

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    Lee, T. H., Ren, B., & Ge, S. S. (2008). Adaptive neural control of SISO time-delay nonlinear systems with unknown hysteresis input. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (1 PART 1 ed.). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 17, No. 1 PART 1). https://doi.org/10.3182/20080706-5-KR-1001.0530