Adaptive neural control of non-affine pure-feedback systems

Gong Wang, David J. Hill, Shuzhi S. Ge

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

3 Citations (Scopus)

Abstract

Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called "ISS-modularity" of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages298-303
Number of pages6
ISBN (Print)0780389360, 9780780389366
DOIs
Publication statusPublished - 2005
Externally publishedYes
EventIEEE International Symposium on Intelligent Control 2005 - Limassol, Cyprus
Duration: 27 Jun 200529 Jun 2005
Conference number: 20th
https://ieeexplore.ieee.org/xpl/conhome/9900/proceeding (Proceedings)

Conference

ConferenceIEEE International Symposium on Intelligent Control 2005
Abbreviated titleISIC '05
Country/TerritoryCyprus
CityLimassol
Period27/06/0529/06/05
Internet address

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