title: High-order sliding-mode control for blood glucose regulation in the presence of uncertain dynamics.
abstract: The success of blood glucose automatic regulation depends on the robustness of the control algorithm used. It is a difficult task to perform due to the complexity of the glucose-insulin regulation system. The variety of model existing reflects the great amount of phenomena involved in the process, and the inter-patient variability of the parameters represent another challenge. In this research a High-Order Sliding-Mode Control is proposed. It is applied to two well known models, Bergman Minimal Model, and Sorensen Model, to test its robustness with respect to uncertain dynamics, and patients' parameter variability. The controller designed based on the simulations is tested with the specific Bergman Minimal Model of a diabetic patient whose parameters were identified from an in vivo assay. To minimize the insulin infusion rate, and avoid the hypoglycemia risk, the glucose target is a dynamical profile.
authors.affiliation: Department of Control, Engineering Faculty, Universidad Nacional Autónoma de México, CP 04510 México DF. anagabygh@gmail.com
authors.forename: Ana Gabriela Gallardo
authors.initials: AG
authors.lastname: Hernández
authors.forename: Leonid
authors.initials: L
authors.lastname: Fridman
authors.forename: Ron
authors.initials: R
authors.lastname: Leder
authors.forename: Sergio Islas
authors.initials: SI
authors.lastname: Andrade
authors.forename: Cristina Revilla
authors.initials: CR
authors.lastname: Monsalve
authors.forename: Yuri
authors.initials: Y
authors.lastname: Shtessel
authors.forename: Arie
authors.initials: A
authors.lastname: Levant
mesh_terms: D000368:Aged; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism*; D006801:Humans; D007003:Hypoglycemia / Q000517:prevention & control*; D007328:Insulin / Q000378:metabolism*; D007332:Insulin Infusion Systems; D008297:Male; D008954:Models, Biological; D035501:Uncertainty
chemical_list: D001786:Blood Glucose; D007328:Insulin