Adaptive sliding mode Gaussian controller for artificial pancreas in TIDM patient

Abstract Optimal closed loop control of blood glucose (BG) level has been a major focus for the past so many years to realize an artificial pancreas for type-I diabetes mellitus (TIDM) patients. There is an urgency for controlled drug delivery system to design with appropriate controller not only to regulate the BG level, but also for other chronic clinical disorders requiring continuous long term medication. As a solution to the above problem, a novel sliding mode Gaussian controller with state estimation (SMGC/SE) is proposed, whose gains dynamically vary with respect to the error signal. For the designing of the SMGC/SE, a nonlinear TIDM patient model is linearized as a 9th order state-space model with a micro-insulin dispenser. This controller is evaluated and compared with other recently published control techniques. Obtained results clearly reveal the better performance of the proposed method to regulate the BG level within the normoglycaemic range in terms of accuracy and robustness.