Abstract
An in-house predictive control algorithm has been implemented to control blood glucose level in type I diabetic patients, by controlling the insulin infusion rate to a mechanical pump. The role of the disturbance filter in model-based predictive control is underlined and its possibility to improve control performance is exploited. For comparison purposes, a classic PID controller has been designed via CAD tools. Controller performance was assessed in terms of its ability to track a normoglycemic setpoint (81mg/dL) from initial states of hypo- and hyperglycemia, as well as in response to a meal disturbance. Unconstrained control gave satisfactory results, within imposed constraints. Both strategies are implemented in discrete manner, thus suitable for future implementation in wearable devices.
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