Investigation on modelling and identification of glucose management system for normal individual and diabetic patient

•Dynamic modelling and identification of glucose management system for normal individual and diabetic patients.•Parameters of the dynamic model are estimated using solver in ordinary differential equations.•Quality of estimation of nonlinear system parameters are validated with the experimental value. This research work pertains to the development and investigation of dynamic modelling and parametric identification of glucose management system for normal individual and diabetic patient. Modelling using Bergman model captures the two minimal models of glucose disappearance and insulin kinetics. The two minimal models of nonlinear glucose management systems are identified using MATLab. The dynamics of glucose management system using first-principle method consisting of one input and two output variables, model is derived. The parameters of the dynamic model are estimated using solver in ordinary differential equations. The dynamic minimal model parameters are identified for both normal individual and diabetic patient. In this article, both the glucose and insulin are estimated for normal individual and diabetic patient. The quality of estimation of nonlinear system parameters are validated with the experimental value. The results obtained from the nonlinear models are in good agreement with the experimental one based on square relative error.