Friday , September 21 2018

Artificial Neural Network Control of the Recycle Compression System

Razika ZAMOUM BOUSHAKI1, Boukhemis CHETATE2, Yasmine ZAMOUM2
1 Institut de Génie Electrique et Electronique,
Université M’hamad Bougara de Boumerdes,
Avenue de l’indépendance, Boumerdes 35000, Algeria,
boushakiraz@yahoo.fr
2 Laboratoire de Recherche sur l’Electrification des Entreprises Industrielles,
Université M’hamad Bougara de Boumerdes,
Avenue de l’indépendance, Boumerdes 35000, Algeria
boukhemis.chetate@gmail.com

Abstract: This paper presents results from an investigation on a nonlinear compressor control. The useful range of operation of turbo compressors is limited by choking at high rate flows and by the onset of instability known as surge at low rate flows. Traditionally, this instability has been avoided by using control systems that prevent the operating point of the compressor to enter in the unstable region. It is not efficient to apply classical controllers, such as simple P, PI and PID when the parameters of compression system change frequently. The aim of our work is to design and simulate an intelligent controller. A simulation part is clearly presented with the advantages of the intelligent system.

Keywords: Compression system, PID controller, Fuzzy logic control, Neural predictive controller, NARMA L2 Control.

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CITE THIS PAPER AS:
Razika ZAMOUM BOUSHAKI, Boukhemis CHETATE, Yasmine ZAMOUM, Artificial Neural Network Control of the Recycle Compression System, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (1), pp. 65-76, 2014.

https://doi.org/10.24846/v23i1y201407