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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In this paper, adaptive neural control is investigated for a class of SISO unknown non-affine nonlinear systems with state time-varying delays and unknown hysteresis input. The non-affine problem is solved by adopting mean value theorem and implicit function theorem. 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 also mitigated through the proposed adaptive control. By utilizing the Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB).

Original languageEnglish
Title of host publication2008 American Control Conference, ACC
Pages4203-4208
Number of pages6
DOIs
StatePublished - 2008
Event2008 American Control Conference, ACC - Seattle, WA, United States
Duration: Jun 11 2008Jun 13 2008

Publication series

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

Conference

Conference2008 American Control Conference, ACC
CountryUnited States
CitySeattle, WA
Period06/11/0806/13/08

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