Parameter identification and state estimation for a diabetic glucose‐insulin model via an adaptive observer
Résumé
In this article, an adaptive observer is designed for patients with Type 1 DiabetesMellitus.
The adaptive observer, synthesized using the so-called Bergman’s
Minimal Model, simultaneously estimates the states and the parameter corresponding
to the insulin-independent glucose disappearance rate. The adaptive
observer dealswith parameter uncertainties,whereas the food intake is regarded
as an external disturbance. The adaptive observer relies on intravenous glucose
measurements. The state estimation error converges to a neighborhood of the
origin despite the effects of the external disturbances and uncertainties, while
the parameter estimation error converges in a fixed time to a neighborhood of the
origin. The adaptive observer synthesis is given by a constructive method based
on linear matrix inequalities. Simulation results show the feasibility of the proposed
scheme. Moreover, the approach is validated in UVA/Padova metabolic
simulator for ten in silico adult patients.