Adaptive neural control for a class of nonlinear systems with uncertain hysteresis inputs and time-varying state delays

Beibei Ren, Shuzhi Sam Ge, Tong Heng Lee, Chun Yi Su

Research output: Contribution to journalArticle

71 Scopus citations

Abstract

In this paper, adaptive variable structure neural control is investigated for a class of nonlinear systems under the effects of time-varying state delays and uncertain hysteresis inputs. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design, and the effect of the uncertain hysteresis with the Prandtl-Ishlinskii (PI) model representation is also mitigated using the proposed control. By utilizing the integral-type Lyapunov function, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded (SGUUB). Extensive simulation results demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)1148-1164
Number of pages17
JournalIEEE Transactions on Neural Networks
Volume20
Issue number7
DOIs
StatePublished - 2009

Keywords

  • Neural networks (NNs)
  • Prandtl-Ishlinskii (PI) hysteresis model
  • Time-varying delays
  • Variable structure control

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