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Stable impulsive zone model predictive control for type 1 diabetic patients based on a long‐term model
Author(s) -
González Alejandro H.,
Rivadeneira Pablo S.,
Ferramosca Antonio,
Magdelaine Nicolas,
Moog Claude H.
Publication year - 2020
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2647
Subject(s) - model predictive control , term (time) , control theory (sociology) , stability (learning theory) , control (management) , insulin , diabetes mellitus , medicine , mathematics , computer science , endocrinology , artificial intelligence , machine learning , physics , quantum mechanics
Summary In this work, the problem of regulating blood glucose (glycemia) in type I diabetic patients is studied by means of an impulsive zone model predictive control (iZMPC), which bases its predictions on a novel long‐term glucose‐insulin model. Taking advantage of the impulsive version of the model—which features real‐life properties of diabetes patients that some other popular models do not—the given control guarantees the stability under moderate‐to‐severe plant‐model mismatch and disturbances. Long‐term scenarios—including meals and physiological parameter variations—are simulated and the results are satisfactory as every hyperglycemic and hypoglycemic episodes are suitably controlled.