Adaptive Neural Control of SISO Time-Delay Nonlinear Systems with Unknown Hysteresis Input

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 func...

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Bibliographic Details
Published inIFAC Proceedings Volumes Vol. 41; no. 2; pp. 248 - 253
Main Authors Lee, Tong Heng, Ren, Beibei, Ge, Shuzhi Sam
Format Journal Article
LanguageEnglish
Published 2008
Subjects
hysteresis
neural networks
Time-vary delays
Time-vary delays
neural networks
hysteresis
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Summary: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.
ISSN:1474-6670
DOI:10.3182/20080706-5-KR-1001.00042