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INFORMATICA, 2014, Vol. 25, No. 3, 401-414
© Institute of Mathematics and Informatics,
DOI: http://dx.doi.org/10.15388/Informatica.2014.20

ISSN 0868-4952

Adaptive Inverse Control Using an Online Learning Algorithm for Neural Networks

José Luis CALVO-ROLLE1, Oscar FONTENLA-ROMERO, Beatriz PÉREZ-SÁNCHEZ, Bertha GUIJARRO-BERDIÑAS

Department of Industrial Engineering, E.U. Politécnica, University of A Coruña Campus de Ferrol, Avda. 19 de Febrero s/n, 15405 Ferrol, Spain Laboratory for Research and Development in Artificial Intelligence (LIDIA) Department of Computer Science, Faculty of Informatics, University of A Coruña Campus de Elviña s/n, 15071 A Coruña, Spain E-mail: jlcalvo@udc.es, ofontenla@udc.es, bperezs@udc.es, cibertha@udc.es

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.

Keywords:

model predictive control, adaptive inverse control, neural networks, neural predictor


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