(494i) Simulation Studies On Nonlinear Control Strategies of Glucose for Type 1 Diabetes Based On Hammerstein Model

In order for an ?artificial pancreas? to become practical for ambulatory use, a closes-loop control strategy for automated insulin delivery must be developed. This paper is concerned with the development of novel nonlinear control strategies for blood glucose control in subjects with type 1 diabetes.

Many physiological models have been proposed which describe glucose and/or insulin dynamics. On the other hand, empirical models for type 1 diabetes have been far less prevalent in the literature. However, empirical models are more attractive than physiological models in the sense that they are often much simpler and thus suitable for control design. In this paper, the simulation studies are based on two physiological models, minimal model [1] and Hovorka model [2]. Due to the nonlinear dynamics of the models, this studies use a Hammerstein system (a static nonlinearity followed by a linear dynamic subsystem) for modeling of the glucose-insulin system. The Hammerstein model has two input variables, the insulin infusion rate and meal CHO amount, and one output variable, the glucose concentration. The model parameters are identified based on the input-output data from simulations using physiological models. The predictive capabilities of glucose concentration using Hammerstein models are investigated. Based on the Hammerstein model, nonlinear control strategies are proposed for blood glucose control. The control strategies consist of a model predictive controller based on real-time glucose measurement and a feedforward controller based on the meal CHO uptake. The main advantage of using Hammerstein model is that the controllers can be designed if a linear system is controlled. The effectiveness of the proposed control strategies is evaluated in simulations.

References:

[1] Bergman RN, Phillips LS, Cobelli C. Physiologic evaluation of factors controlling glucose tolerance in man. J. Clin. Invest., 68(1981),1456-1467.

[2] Hovorka R, Canonico V, J Chassin LJ, Haueter U, Massi-Benedetti M, Federici MO, Pieber TR, Schaller HC, Schaupp L, Vering T, Wilinska ME. Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. Physiol. Meas., 25(2004), 905-920.