Commande prédictive approximante.

Boumaza, Hamza; Belarbi, Khaled

dc.contributor.author	Boumaza, Hamza
dc.contributor.author	Belarbi, Khaled
dc.date.accessioned	2022-05-24T09:57:52Z
dc.date.available	2022-05-24T09:57:52Z
dc.date.issued	2013-11-21
dc.identifier.uri	http://depot.umc.edu.dz/handle/123456789/5990
dc.description	52 f.
dc.description.abstract	Predictive control is by far the best known method in industry for its tolerance towards different types of systems and the constraints imposed. Nevertheless, it is these limitations upwind speed systems. We propose in this work an approach that is based on the approximate predictive control by fuzzy learning. The optimal predictive control law obtained off line using simulation model is used as data base for training the fuzzy system. Simulations were performed to illustrate the interest of our approach and its validation.
dc.format	30 cm.
dc.language.iso	fr
dc.publisher	Université Frères Mentouri - Constantine 1
dc.subject	Electronique
dc.subject	Electronique: Contrôle des systèmes
dc.subject	Commande prédictive
dc.subject	Commande prédictive explicite
dc.subject	Commande Prédictive Approximante
dc.subject	Apprentissage flou
dc.subject	Model Predictive Control
dc.subject	Explicit MPC
dc.subject	Approximate Predictive Control
dc.subject	Takagi Sugeno Fuzzy learning
dc.subject	التحكم التنبؤي
dc.subject	التحكم التنبؤي المقرب
dc.subject	التدریب النظام الضبابي
dc.title	Commande prédictive approximante.
dc.type	Thesis
dc.coverage	2 copies imprimées disponibles