A new characterization of stable neural network control for discrete-time uncertain systems

Tomohisa Hayakawa, Wassim M. Haddad, Naira Hovakimyan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A novel neuro adaptive control framework for discrete-time multivariable nonlinear uncertain systems is developed. The proposed framework is Lyapunov-based and guarantees, instead of ultimate boundedness, partial asymptotic stability of the closed-loop system; that is, Lyapunov stability of the closed-loop system states and attraction with respect to the plant states. Unlike standard neural network approximation, we assume that the approximation error can be confined in a small gain-type norm-bounded conic sector over a compact set. This helps to couple tools from robust control with adaptive laws in discrete time to prove partial asymptotic stability of the closed-loop system. Finally, an illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.

Original languageEnglish (US)
Title of host publicationProceedings of the 16th IFAC World Congress, IFAC 2005
Pages324-329
Number of pages6
StatePublished - Dec 1 2005
Externally publishedYes
Event16th Triennial World Congress of International Federation of Automatic Control, IFAC 2005 - Prague, Czech Republic
Duration: Jul 3 2005Jul 8 2005

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume16
ISSN (Print)1474-6670

Other

Other16th Triennial World Congress of International Federation of Automatic Control, IFAC 2005
CountryCzech Republic
CityPrague
Period7/3/057/8/05

Keywords

  • Adaptive control
  • Asymptotic stability
  • Discrete-time systems
  • Lyapunov method
  • Neural network
  • Sector-bounded nonlinearities

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Hayakawa, T., Haddad, W. M., & Hovakimyan, N. (2005). A new characterization of stable neural network control for discrete-time uncertain systems. In Proceedings of the 16th IFAC World Congress, IFAC 2005 (pp. 324-329). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 16).