Self tuning control of nonlinear systems based on artificial neural network models

M. Kenmal Ciliz, Hari Krishna, Can Isik

Research output: Contribution to journalConference article

1 Scopus citations

Abstract

The authors address the tracking control of nonlinear systems with unknown dynamics. A self-tuning control architecture is proposed based on the nonlinear computational properties of artificial neural networks. A local convergence analysis of the weight update equations is given and then the algorithm is simulated and successfully tested for discrete time nonlinear systems.

Original languageEnglish (US)
Pages (from-to)980-984
Number of pages5
JournalConference Record - Asilomar Conference on Circuits, Systems & Computers
Volume2
StatePublished - Dec 1 1991
Event24th Asilomar Conference on Signals, Systems and Computers Part 2 (of 2) - Pacific Grove, CA, USA
Duration: Nov 5 1990Nov 7 1990

ASJC Scopus subject areas

  • Engineering(all)

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