Nonlinear adaptive control design using on-line trained neural networks

Research output: Contribution to journalConference articlepeer-review

Abstract

An artificial feedforward neural network is used for on-line control of a certain class of partially known single-input, single-output dynamic systems. The neural network's task is to provide an approximation of the unknown input-output behavior of the dynamic system to the controller in order to drive the system's behaviour according to specifications given by a reference model. The error correction-based learning algorithm used to update the weights of the single layer neural network used in the control scheme allows dynamic adjustment of their values to cope with varying signals coming from the dynamic plant.

Original languageEnglish (US)
Pages (from-to)1453-1457
Number of pages5
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume2
StatePublished - 1994
Externally publishedYes
EventProceedings of the 1994 IEEE International Conference on Systems, Man and Cybernetics. Part 1 (of 3) - San Antonio, TX, USA
Duration: Oct 2 1994Oct 5 1994

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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