Wild Goat Optimization based Adaptive Controller for BG Regulation in TIDM Patient

Abstract: This study proposes a Wild Goat Optimization-Tilt Acceleration-Derivative-Filter (WGO-TADF) controller for robust regulation of Blood Glucose (BG) levels in patients with Type-I Diabetes Mellitus (TIDM) using an Artificial Pancreas (AP). Backgrounds: TIDM is a chronic condition marked by the body's inability to produce insulin, leading to dangerous fluctuations in BG levels. Maintaining normo-glycemia (70-120 mg/dl) is challenging due to nonlinear physiological responses and external disturbances like meals and exercise. Existing control strategies, such as PID, Fuzzy, LQG, and H∞ controllers, often fall short in providing the adaptive tuning, global robustness, and rapid convergence required for accurate BG regulation. Therefore, advanced control strategies integrated with optimization algorithms are essential to improve glycemic control in TIDM patients. This study proposes a WGO-TADF controller for robust regulation of BG levels in TIDM patients with an AP. Objective: The primary objective is to develop a controller that ensures normo-glycemia while enhancing stability, accuracy, and robustness under physiological uncertainties and external disturbances. The WGO algorithm tunes the control gains of the TADF controller to minimize the objective function, ensuring optimal insulin infusion in real time. The WGO-TADF controller introduces a filtered structure to improve the dynamic response and noise rejection capability, effectively handling the nonlinear nature of GI dynamics. Methods: Briefly describes the use of the WGO algorithm to tune the proposed TADF controller integrated into an AP framework. Results: Simulation results demonstrate that the proposed approach (WGO-TADF) achieves a faster settling time (228 min), lower peak overshoot (3.8 mg/dl), and reduced noise (1%) compared to other existing control strategies. Conclusion: The closed-loop patient model achieves a stable BG level of 81 mg/dl under varying meal and exercise disturbances, validating the superior performance and robustness of the WGO-TADF approach.