Research on Blood Glucose Regulation of Type I Diabetes Based on Adaptive RBF Network

A backstepping control algorithm based on an adaptive RBF neural network is proposed for the glucose regulation problem in type I diabetes. Firstly, the complex mechanism of glucose-insulin action in human body is described based on Bergman minimum model; secondly, the RBF neural network are used to approximate the nonlinear functions in Bergman’s mini-mum model, then the adaptive rate of the proposed algorithm is derived and the controller is designed based on the backstepping method to ensure the stability and convergence of the whole system; finally, the validation are performed by MATLAB and compared with the results of blood glucose control in recent years. The final results show that the controller has the advantages of fast convergence, insensitivity to external interference and small control quantity.