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- W2050280504 abstract "In this paper, inverse optimal neural control for trajectory tracking is applied to glycemic control of type 1 diabetes mellitus (T1DM) patients. The proposed control law calculates the adequate insulin delivery rate in order to prevent hyperglycemia and hypoglycemia levels in T1DM patients. Two models are used: (1) a nonlinear compartmental model in order to obtain type 1 diabetes mellitus virtual patient behavior, and (2) a neural model obtained from an on-line neural identifier, which uses a recurrent neural network, trained with the extended Kalman filter (EKF); the last one allows the applicability of an inverse optimal neural controller. The proposed algorithm is tuned to track a desired trajectory; this trajectory reproduces the glucose absorption of a healthy person. The applicability of the proposed control scheme is illustrated via simulations." @default.
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- W2050280504 date "2012-06-01" @default.
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- W2050280504 title "Inverse optimal neural control of blood glucose level for type 1 diabetes mellitus patients" @default.
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- W2050280504 doi "https://doi.org/10.1016/j.jfranklin.2012.02.011" @default.
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