Diabetes mellitus affected an estimated 463 million people in the year 2019. The number of diabetic patients is projected to increase to an alarming figure of 700 million by the year 2045, out of which 90–95% of them are expected to be type 2 diabetes mellitus (T2DM) patients. The research presented an alternative way of state-of-the-art insulin therapy using manual insulin infusion. The T2DM model that simulates the body reaction of a T2DM patient has been developed using real human clinical data that uses insulin pump therapy. The proposed system uses a closed-loop control together with fuzzy gain scheduling and recurrent self-evolving Takagi–Sugeno–Kang fuzzy neural network (RST-FNN). Such a system will help the patient remove the need for manual insulin infusion. This proposed system will record the blood glucose level and predict the next iteration’s blood glucose level. The change in blood glucose level will help detect the food intake (carbohydrates) with reference to the gain scheduler and the controller will communicate with the insulin pump to infuse the corresponding amount of insulin.