The objective is to design a fully automated glycemia regulation of Type-1 Diabetes (T1D) in both fasting and postprandial phases on a large number of virtual patients. A model-free intelligent PID (iPID) is used to infuse insulin. The feasibility is tested in silico on two simulators with and without measurement noise. The first simulator is derived from a long-term linear time-invariant model. The controller is also validated on the UVa/Padova metabolic simulator on 10 adults under 25 runs/subject for noise robustness test. It is shown that without measurement noise, iPID mimicked the normal pancreatic secretion: a fast rate occurs immediately after meals; it becomes moderate when glycemia decays and reduces to a steady basal mode during fasting. With the UVa/Padova simulator, the robustness against CGM noise and delays was tested. A higher percentage of time in target was obtained with iPID as compared to standard PID with reduced time spent in hyperglycemia.Two different T1D simulators tests showed that iPID detects meals and reacts faster to meal perturbations as compared to a classic PID. The intelligent part turns the controller to be more aggressive immediately after meals without neglecting safety. Thus, postprandial hyperglycemia is reduced with less late postprandial hypoglycemia. The simple structure iPID is a step for PID like controllers since it combines the classic PID nice properties with new adaptive features.