Adaptive neural control for a class of nonlinearly parametric time-delay systems : First order case

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages3304-3308
Volume4
Publication statusPublished - 2002

Publication series

Name
Volume4

Conference

TitleProceedings of the 4th World Congress on Intelligent Control and Automation
PlaceChina
CityShanghai
Period10 - 14 June 2002

Abstract

In this paper, an adaptive neural controller for a class of first-order time-delay nonlinear systems with unknown nonlinearities is proposed. Based on WNN (Wavelet Neural Network) on-line approximation model, a state-feedback adaptive controller is obtained by constructing an novel integral-type Lyapunov-Krasovskii functional. The key assumption is that the time-delay term of the systems satisfies a certain inequality condition. The proposed method guarantees semi-global uniform ultimate boundedness for the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.

Citation Format(s)

Adaptive neural control for a class of nonlinearly parametric time-delay systems: First order case. / Ho, D. W C; Li, Junmin.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA). Vol. 4 2002. p. 3304-3308.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review