| Titre : | Nonlinear predictive control application to a solar thermal process : Commande prédictive non-linéaire application à un processus solaire thermique |
| Auteurs : | Yassine Himour, Auteur ; Mohamed Tadjine, Directeur de thèse ; Mohamed Seghir Boucherit, Directeur de thèse |
| Type de document : | document électronique |
| Editeur : | [S.l.] : [s.n.], 2025 |
| Format : | 1 fichier PDF (2.8 Mo) / ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet
Thèse de Doctorat : Automatique : Alger, Ecole Nationale Polytechnique : 2025 Bibliogr. p. 101-112 -annexe |
| Langues : | Anglais |
| Index. décimale : | D001825 |
| Tags : | Nonlinear predictive control Infinite gain scheduling Neural networks Parabolic solar trough. |
| Résumé : |
Solar thermal plants have high nonlinearities and non-manipulated energy source which
make their control task a very challenging work. Linear controllers can’t cope with undesirable deviations of the outlet temperature over all the operation range of the dynamics of this type of plants. Moreover, nonlinear predictive control relying on online nonlinear optimisation have the drawback of time consuming and numerical calculus issues. In this work, neural nonlinear predictive control and an infinite gain scheduling neural predictive control are designed and applied to control the temperature in a distributed parabolic trough solar collector field. The performance of both tracking and disturbance rejection of the proposed controller is compared to those the nonlinear predictive control strategies. The superiority of the proposed control strategy is well demonstrated through some indices in simulation results. The thesis concludes with recommendations and perspectives for future works. |
Exemplaires (1)
| Cote | Support | Localisation | Section | Disponibilité | Spécialité | Etat_Exemplaire |
|---|---|---|---|---|---|---|
| D001825 | Ressources électroniques | Bibliothèque centrale | Thèse de Doctorat | Disponible | Automatique | Téléchargeable |
