The 'Type 1 Diabetes Mellitus (T1DM)' is a dangerous illness that concerns yearly increasing population. The control of the glucose level in the human body is a widely investigated subject area that also has serious technical difficulties as the lack of reliable system model for each individual patient, the limitations regarding the observability of the complete internal state of the patient (at least in the view of the system model). On this reason the 'Model Predictive Control (MPC)' needs either robust or adaptive completion in this field of application. In the lack of observable data the traditional state estimators may have only limited relevance. The 'Robust Fixed Point Transformation (RFPT)' based method was elaborated for the design of adaptive controllers typically for such situations. It does not need any sophisticated system model, it can work on the basis of observations that concern only the controlled quantity without the need of complete state estimation. In the present paper the use of the RFPT-based adaptive controller is reported in simulation investigations in which the validity of Bergman's 'Minimal Model' is assumed. Promising simulation results are presented.