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Article type: Research Article
Authors: Calvo-Rolle, José Luis; | Fontenla-Romero, Oscar | Pérez-Sánchez, Beatriz | Guijarro-Berdiñas, Bertha
Affiliations: Department of Industrial Engineering, E.U. Politécnica, University of A Coruña, Campus de Ferrol, Avda. 19 de Febrero s/n, 15405 Ferrol, Spain, e-mail: jlcalvo@udc.es | 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: ofontenla@udc.es, bperezs@udc.es, cibertha@udc.es
Note: [] Corresponding author.
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
Journal: Informatica, vol. 25, no. 3, pp. 401-414, 2014
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