A model-based algorithm for blood glucose control in type I diabetic patients
A model-based algorithm for blood glucose control in type I diabetic patients
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DOI:
10.1109/10.740877
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发表时间:
1999-02-01
影响因子:
4.6
通讯作者:
Peppas, NA
中科院分区:
文献类型:
--
作者:
Parker, RS;Doyle, FJ;Peppas, NA
A model-based predictive control algorithm is developed to maintain normoglycemia in the Type I diabetic patient using a closed-loop insulin infusion pump, Utilizing compartmental modeling techniques, a fundamental model of the diabetic patient is constructed. The resulting nineteenth-order nonlinear pharmacokinetic-pharmacodynamic representation is used in controller synthesis. Linear identification of an input-output model from noisy patient data is performed by filtering the impulse-response coefficients via projection onto the Laguerre basis. A linear model predictive controller is developed using the identified step response model. Controller performance for unmeasured disturbance rejection (50 g oral glucose tolerance test) is examined. Glucose setpoint tracking performance is improved by designing a second controller which substitutes a more detailed internal model including state-estimation and a Kalman filter for the input-output representation, The state-estimating controller maintains glucose within 15 mg/dl of the setpoint in the presence of measurement noise, Under noise-free conditions, the model based predictive controller using state estimation outperforms an internal model controller from literature (49.4% reduction in undershoot and 45.7% reduction in settling time), These results demonstrate the potential use of predictive algorithms for blood glucose central in an insulin infusion pump.