Adaptive Control with Disturbance Modelling for BG Regulation in TIDM Patient

In order to control blood glucose levels in TIDM patients, this paper explains the creation of a Teaching Learning Based Optimization-PID (TLBO-PID) controller that delivers appropriate insulin doses through an artificial pancreas (AP). Using the Teaching Learning Based Optimization (TLBO), that adjusts the controller gains to improve the BG control of the proposed patient model. This classic controller with TLBO is intended to increase the performance and toughness of patient's problems with glycemic management which are resulting from nonlinearities in the patient model. The nonlinearity of patient models can be effectively handled by using an AP-based TLBO, which also helps to keep blood sugar levels in the glycemic range (70–120 mg/dL). The accuracy, robustness, stability, noise reduction, and enhanced capacity to handle uncertainties are examined while using the proposed patient model with TLBO-PID. A comparison of data from different control strategies indicates the reasons for the suggested approach's superior control performance.