Impact of disturbance filter in nonlinear EPSAC predictive control of blood glucose level in type I diabetic patients

Abstract

The nonlinear EPSAC (NEPSAC) predictive control algorithm has been implemented to regulate blood glucose level in type I diabetic patients, by controlling the insulin infusion rate with a micropump. The advantage of the NEPSAC strategy is that the nonlinear process is never linearized, thus it uses directly the nonlinear patient model. The role of the disturbance filter in model-based predictive control is underlined and its possibility to improve control performance is exploited. A default disturbance filter, consisting of an integrator to ensure zero steady-state error, is compared to an intelligent filter design with and without output constraints. Controller performance was assessed in terms of its ability to reject a meal disturbance of 30 g glucose.