| Titre : |
Fractional-Order Adaptive Control Techniques for Artificial Pancreas |
| Titre original : |
Techniques adaptatives d’ordre fractionnaire appliquées à un pancréas |
| Type de document : |
document électronique |
| Auteurs : |
Serine Bensalem, Auteur ; Abir Boukaba, Auteur ; Ladaci, Samir, Directeur de thèse |
| Editeur : |
[S.l.] : [s.n.] |
| Année de publication : |
2025 |
| Importance : |
1 fichier PDF (14;8 Mo) |
| Présentation : |
ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 116 - 122 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Artificial Pancreas
Fractional Calculus
Adaptive Control
Sliding Mode Control
Bergman
Minimal Model
IVTT Model
Robustness Test
Meal Intake
Adaptive Neuro Fuzzy Controller
Genetic Algorithm
Optimization |
| Résumé : |
Type 1 diabetes mellitus is a disease where the patient is not able to produce necessary insulin
to regulate the concentration of glucose in the blood. Artificial pancreas is a device that can
regulate this concentration and turn the behavior to normal. The human regulatory system can
be modeled using differential equations; their order could be integer or fractional. In this work,
we examine the accuracy of fractional-order modeling of the minimal model using real data, then
robust control techniques are implemented. First, a model reference indirect adaptive controller
is designed using two approaches: integer order approach and fractional-order approach, then a
fractional-order sliding mode controller is implemented with a robust sliding mode observer to
estimate the glucose concentration in the blood. The controller is tuned by a genetic optimization
algorithm. Finally, a Neuro fuzzy controller. Several robustness tests are presented (Meal
simulation) and evaluated using different types of errors’ criteria. |
Fractional-Order Adaptive Control Techniques for Artificial Pancreas = Techniques adaptatives d’ordre fractionnaire appliquées à un pancréas [document électronique] / Serine Bensalem, Auteur ; Abir Boukaba, Auteur ; Ladaci, Samir, Directeur de thèse . - [S.l.] : [s.n.], 2025 . - 1 fichier PDF (14;8 Mo) : ill. Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 116 - 122 Langues : Anglais ( eng)
| Mots-clés : |
Artificial Pancreas
Fractional Calculus
Adaptive Control
Sliding Mode Control
Bergman
Minimal Model
IVTT Model
Robustness Test
Meal Intake
Adaptive Neuro Fuzzy Controller
Genetic Algorithm
Optimization |
| Résumé : |
Type 1 diabetes mellitus is a disease where the patient is not able to produce necessary insulin
to regulate the concentration of glucose in the blood. Artificial pancreas is a device that can
regulate this concentration and turn the behavior to normal. The human regulatory system can
be modeled using differential equations; their order could be integer or fractional. In this work,
we examine the accuracy of fractional-order modeling of the minimal model using real data, then
robust control techniques are implemented. First, a model reference indirect adaptive controller
is designed using two approaches: integer order approach and fractional-order approach, then a
fractional-order sliding mode controller is implemented with a robust sliding mode observer to
estimate the glucose concentration in the blood. The controller is tuned by a genetic optimization
algorithm. Finally, a Neuro fuzzy controller. Several robustness tests are presented (Meal
simulation) and evaluated using different types of errors’ criteria. |
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