Geometric adaptive control in type 1 diabetes

G. R. Cocha; C. Amorena; A. Mazzadi; C. D'Attellis

doi:10.1117/12.2256677

26 January 2017 Geometric adaptive control in type 1 diabetes

G. R. Cocha, C. Amorena, A. Mazzadi, C. D'Attellis

Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 101600R (2017) https://doi.org/10.1117/12.2256677
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina

Abstract

In geometric control model based methods, it is well known that if a nonlinear system has its relative degree equal to the number of states in the neighborhood of a point of equilibrium, thus it is possible to perform a coordinate transformation and a state feedback that transforms the nonlinear system into a linear and controllable one. Stabilization of this system is possible by a simple linear control technique. This method is based on the exact cancellation of nonlinear terms. If the parameters are either time-varying or there is uncertainty in the nonlinear terms of the model, then cancellation would not be longer accurate. The modification of the control method with adaptive parameters, makes asymptotically exact the cancellation of the nonlinear terms and maintains the efficiency of the transformation. This paper presents a nonlinear adaptive control method based on exact linearization techniques applied to the automation of blood glucose regulation in Type-1 diabetes. Using continuous blood glucose monitoring as the input, the method provides the insulin infusion function as the output. Since the insulin infusion calculated drives blood glucose to normal levels, the method mimics the healthy pancreas function and it could be applied in artificial pancreas to control blood glucose in type 1 diabetic patients.

Citation Download Citation

G. R. Cocha, C. Amorena, A. Mazzadi, and C. D'Attellis "Geometric adaptive control in type 1 diabetes", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101600R (26 January 2017); https://doi.org/10.1117/12.2256677

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available