Constrained Linear Model Predictive Control for an Artificial Pancreas

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dc.authorscopusid57220781829
dc.authorscopusid58087496900
dc.authorscopusid59162501500
dc.authorscopusid18038472600
dc.authorscopusid59163414200
dc.authorscopusid59162731100
dc.authorscopusid16246029600
dc.contributor.authorArbi, Khadidja Fellah
dc.contributor.authorMorakchi, Mohamed Razi
dc.contributor.authorEl Aouaber, Zineb Aziza
dc.contributor.authorSaffih, Faycal
dc.contributor.authorDjaddoudi, Mohammed Sobir
dc.contributor.authorBouregaa, Mohammed
dc.contributor.authorSoulimane, Sofiane
dc.date.accessioned2024-09-11T19:59:02Z
dc.date.available2024-09-11T19:59:02Z
dc.date.issued2024
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024 -- 21 April 2024 through 22 April 2024 -- Biskra -- 199870en_US
dc.description.abstractThe achievement of closed-loop glycemic control, and hence the automation of insulin administration, is highly required in the implementation of an Artificial Pancreas system. Various control theory approaches have been employed in numerous attempts to design an appropriate control algorithm. In our study, we adopted a Constrained linear model predictive controller (CLMPC). Our simulations have shown that the Constrained LMPC algorithm performs exceptionally well in maintaining blood glucose levels for patients across different scenarios. It effectively manages measurement and process noise, which is crucial for the practical implementation of the system. Moreover, the incorporation of feedforward capability in the controller has shown significant benefits, enabling proactive planning for future meals and optimizing blood glucose levels. Our CLMPC is more effective and very simple than the one presented in the literature, making it suitable for simple smartphone applications that support diabetes self-management. © 2024 IEEE.en_US
dc.identifier.doi10.1109/ISPA59904.2024.10536796
dc.identifier.isbn979-835030924-9en_US
dc.identifier.scopus2-s2.0-85195381611en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISPA59904.2024.10536796
dc.identifier.urihttps://hdl.handle.net/11363/8621
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectArtificial Pancreas; Automatic Insulin Delivery; Closed-loop system; Control Algorithm; Model Predictive Controlen_US
dc.titleConstrained Linear Model Predictive Control for an Artificial Pancreasen_US
dc.typeConference Objecten_US

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