Synergetic and higher order sliding mode control of blood glucose regulation in diabetes patients

Diabetes mellitus is a chronic disorder of carbohydrate metabolism due to relative or absolute insulin deficiency. This latter can be best handled in an automatic procedure. It's essential that control used in such a scheme be robust to any kind of disturbances and parameters uncertainties. In this paper, Bergman's minimal model is used as a starting point in an effort to regulate efficiently glucose level using synergetic control which is then compared to the application of second order sliding mode. These two proven robust control techniques can handle adequately uncertainties to a great extent through their invariance properties. Our contribution shows that synergetic methodology provides better performance. It is obvious that obtaining system parameters exact values is unrealistic in most biological systems, therefore all model parameters will be considered uncertain. Parametric uncertainty will be exploited in developing a control scheme based on a closed-loop feedback strategy. The behavior of the obtained controller is analyzed on its ability to track a normoglycemic in presence of disturbance and perturbed parameters. A comparative study of the application of the two techniques is carried out showing through simulation results that the synergetic control approach offers stronger robustness in performance compared to sliding mode control, despite disturbances.