Key result
The proposed robust adaptive neural network feedback-linearization controller successfully regulated simulated blood glucose levels to the desired target of 90 mg/dl despite meal disturbances and model uncertainties.
A proposed robust adaptive neural network controller based on feedback-linearization effectively regulates simulated blood glucose levels in a Type 1 diabetes model despite uncertainties and meal disturbances.
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Kouchaki et al. (2022) studied Type 1 Diabetes Mellitus. Robust adaptive neural network feedback-linearization controller vs. Sliding mode control was evaluated on Blood glucose regulation to desired level (90 mg/dl). The proposed robust adaptive neural network feedback-linearization controller successfully regulated simulated blood glucose levels to the desired target of 90 mg/dl despite meal disturbances and model uncertainties.
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