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The focus of this paper is on the development of a chance constrained controller for type 1 diabetic patients in the presence of model, meal and initial condition uncertainty. Since the chance constraints require the mean and variance of the evolving uncertain blood-glucose, a conjugate unscented transform based approach is used to estimate the blood-glucose statistics. The proposed approach is demonstrated on the classic Bergman model augmented with a gut dynamics model.
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HYPO/HYPERGLYCEMIC CONSTRAINED DESIGN OF IV INSULIN CONTROL FOR TYPE 1 DIABETIC PATIENTS WITH MEAL AND INITIAL CONDITION UNCERTAINTIES USING SEQUENTIAL QUADRATIC PROGRAMMING
The focus of this paper is on the development of an open loop controller for type 1 diabetic patients which is robust to meal and initial condition uncertainties in the presence of hypoand hyperglycemic constraints. Bernstein polynomials are used to parametrize the evolving uncertain blood-glucose. The unique bounding properties of these polynomials are then used to enforce the desired glycemic constraints. A convex optimization problem is posed in the perturbation space of the model and is solved repeatedly to sequentially converge on a sub-optimal solution. The proposed approach is demonstrated on the classic Bergman model for Type 1 diabetic patients.
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- Award ID(s):
- 1537210
- PAR ID:
- 10113130
- Date Published:
- Journal Name:
- ASME 2018 International Mechanical Engineering Congress and Exposition.
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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