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Adaptive Inverse Control Using an Online Learning Algorithm for Neural Networks
Volume 25, Issue 3 (2014), pp. 401–414
José Luis Calvo-Rolle   Oscar Fontenla-Romero   Beatriz Pérez-Sánchez   Bertha Guijarro-Berdiñas  

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https://doi.org/10.15388/Informatica.2014.20
Pub. online: 1 January 2014      Type: Research Article     

Received
1 June 2012
Accepted
1 April 2014
Published
1 January 2014

Abstract

We propose an adaptive inverse control scheme, which employs a neural network for the system identification phase and updates its weights in online mode. The theoretical basis of the method is given and its performance is illustrated by means of its application to different control problems showing that our proposal is able to overcome the problems generated by dynamic nature of the process or by physical changes of the system which originate important modifications in the process. A comparative experimental study is presented in order to show the more stable behavior of the proposed method in several working ranks.

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Keywords
model predictive control adaptive inverse control neural networks neural predictor

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INFORMATICA

  • Online ISSN: 1822-8844
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