| 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 |
| Année de publication : | 2025 |
| Format : | 1 fichier PDF (14;8 Mo) / 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 |
| Tags : | 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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