Maximum entropy adaptive control of chaotic systems

Jiann Horng Lin, Can Isik

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

6 Scopus citations

Abstract

In this paper, we present an adaptive control strategy for controlling chaos in nonlinear dynamical systems. The proposed method is a neuro-fuzzy model as a globally coupled map based on entropy optimization, which combines an identified system fuzzy model and a control input update rule. The stability analysis of the resulting control scheme is shown by a property of contraction mappings. Numerical examples are given to illustrate the transition between chaotic states and stable equilibrium states.

Original languageEnglish (US)
Title of host publicationIEEE International Symposium on Intelligent Control - Proceedings
PublisherIEEE Computer Society
Pages243-246
Number of pages4
StatePublished - 1998
EventProceedings of the 1998 IEEE International Symposium on Intelligent Control, ISIC - Gaithersburg, MD, USA
Duration: Sep 14 1998Sep 17 1998

Other

OtherProceedings of the 1998 IEEE International Symposium on Intelligent Control, ISIC
CityGaithersburg, MD, USA
Period9/14/989/17/98

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering

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  • Cite this

    Lin, J. H., & Isik, C. (1998). Maximum entropy adaptive control of chaotic systems. In IEEE International Symposium on Intelligent Control - Proceedings (pp. 243-246). IEEE Computer Society.