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Document IIF

Utilisation des réseaux neuronaux et des systèmes experts pour réguler une machine frigorifique à sorption gaz/solide.

Use of neural networks and expert systems to control a gas/solid sorption chilling machine.

Auteurs : PALAU A., VELO E., PUIGJANER L.

Type d'article : Article, Article de la RIF

Résumé

This work focuses on using neural networks and expert systems to control a gas/solid sorption chilling machine. In such systems, the cold production changes cyclically with time due to the batchwise operation of the gas/solid reactors. The accurate simulation of the dynamic performance of the chilling machine has proven to be difficult for standard computers when using deterministic models. Additionally, some model parameters dynamically change with the reaction advancement. A new modelling approach is presented to simulate the performance of such systems using neural networks. The backpropagation learning rule and the sigmoid transfer function have been applied in feedforward, full connected, single hidden layer neural networks. Overall control of this system is divided in three blocks: control of the machine stages, prediction of the machine performance and fault diagnosis.

Documents disponibles

Format PDF

Pages : 59-66

Disponible

  • Prix public

    20 €

  • Prix membre*

    Gratuit

* meilleur tarif applicable selon le type d'adhésion (voir le détail des avantages des adhésions individuelles et collectives)

Détails

  • Titre original : Use of neural networks and expert systems to control a gas/solid sorption chilling machine.
  • Identifiant de la fiche : 1999-0827
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 22 - n. 1
  • Date d'édition : 01/1999

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