Robust nonlinear control of blood glucose in diabetic patients subject to model uncertainties

• Published in: ISA transactions Vol. 133; pp. 353 - 368
• Main Authors: Farahmand, Bahareh, Dehghani, Maryam, Vafamand, Navid, Mirzaee, Alireza, Boostani, Reza, Pieper, Jeffrey Kurt
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.02.2023
• Subjects: Backstepping control; Glucose–insulin​ model; Multi-compartment model; Parametric uncertainties; Robust control; Type 1 diabetes mellitus; UKF estimator; Robust control; Backstepping control; Glucose–insulin​ model; UKF estimator; Multi-compartment model; Parametric uncertainties; Type 1 diabetes mellitus
• ISSN: 0019-0578; 1879-2022; 1879-2022
• DOI: 10.1016/j.isatra.2022.07.009

Recent advances in the artificial pancreas system provide an emerging treatment option for type 1 diabetes. The performance of the blood glucose regulation directly relies on the accuracy of the glucose–insulin modeling. Sorenson model involves the behavior of different organs and offers precise representation. However, the high complexity of such a model makes the controller design procedure a hard task. Therefore, the high-order nonlinear Sorensen model as a popular high-fidelity physiological model is opted in this paper to analyze the glucose–insulin interactions in great detail, and a new robust nonlinear approach to regulate the blood glucose concentration (BGC) in Type-I diabetic patients is proposed. Inspiring the backstepping technique, for designing an acceptable controller, the model is divided into three main subsystems such that in each subsystem, the virtual control input laws are obtained using both Lyapunov stability and input-to-state theorems. Since the measurement of the parameters in the glucose–insulin system is not accurate, parametric uncertainties are defined in the investigated model. Furthermore, owing to the fact that the only measurable state variable is blood glucose, the estimation of inaccessible state variables is an important issue that is properly considered by the unscented Kalman filter (UKF) estimator. The suggested approach is compared to H∞, robust H∞, and linear parameter-varying control approaches. The comparison results on 500 simulated patients imply a remarkable superiority of the proposed controller approach to the compared methods in terms of the BGC tracking and the algorithm robustness in the presence of food intake disturbance patterns. •A novel robust nonlinear controller for the 19-order uncertain nonlinear model of diabetic patients is designed.•The system is divided into three nonlinear subsystems and, virtual control inputs are designed.•The interactions between different subsystems are taken into account in the controller design procedure.•The controller designs the insulin injection plan to regulate the blood glucose level.