PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

Observer-based linear state-dependent control for blood glucose regulation in type 1 diabetic patients with unknown delays

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents a control strategy for blood glucose regulation in the presence of a time-varying delayed input, where the delay is unknown. The proposed control scheme is based on an observer-based linear state-dependent (LSD) (a subclass of the general linear parameter varying (LPV) framework) control with 𝐻 criterion. This proposed control regulates glucose levels in response to meal intake. A novel LSD system representation is used to relax the inherent conservativeness of the nonlinear system. First, the observer achieves an estimate of the current state vector despite the delayed input, where the time-varying unknown delay can be relatively long. Thus, the control law will perform well in the presence of a long unknown delay. The observer-based control scheme is validated by considering different meal disturbances and unknown delay scenarios.
Twórcy
  • Tecnológico Nacional de México, IT Hermosillo, Av. Tec. 115, Hermosillo, 83170, Sonora, Mexico
autor
  • Faculty of Science and Technology, Department of Electrical Engineering, Abdelhamid Ibn Badis University of Mostaganem, Belhacel road, Mostaganem, 27000, Algeria
  • Tecnológico Nacional de México, IT Hermosillo, Av. Tec. 115, Hermosillo, 83170, Sonora, Mexico
  • Tecnológico Nacional de México, IT Hermosillo, Av. Tec. 115, Hermosillo, 83170, Sonora, Mexico
  • Tecnológico Nacional de México, IT Hermosillo, Av. Tec. 115, Hermosillo, 83170, Sonora, Mexico
  • IIxM SECIHTI-Tecnológico Nacional de México, IT Hermosillo, Av. Tec. 115, Hermosillo, 83170, Sonora, Mexico
Bibliografia
  • [1] Röder PV, Wu B, Liu Y, Han W. Pancreatic regulation of glucose homeostasis. Exp Mol Med 2016;48(3):e219.
  • [2] DiMeglio LA, Evans-Molina C, Oram RA. Type 1 diabetes. Lancet 2018;391(10138):2449-62.
  • [3] Association AD. 2. Classification and diagnosis of diabetes: Standards of medical care in diabetes-2021. Diabetes Care 2020;44(Supplement 1):15-33.
  • [4] Hettiarachchi C, Daskalaki E, Desborough J, Nolan CJ, O’Neal D, Suominen H. Integrating multiple inputs into an artificial pancreas system: Narrative literature review. JMIR Diabetes 2022;7(1):e28861.
  • [5] Segil J. Handbook of biomechatronics. Academic Press; 2018.
  • [6] Alonso-Bastida A, Adam-Medina M, Posada-Gómez R, Salazar-Piña DA, Osorio- Gordillo G-L, Vela-Valdés LG. Dynamic of glucose homeostasis in virtual patients: A comparison between different behaviors. Int J Environ Res Public Heal 2022;19(2):716.
  • [7] Mehmood S, Ahmad I, Arif H, Ammara UE, Majeed A. Artificial pancreas control strategies used for type 1 diabetes control and treatment: A comprehensive analysis. Appl Syst Innov 2020;3(3).
  • [8] Quiroz G. The evolution of control algorithms in artificial pancreas: A historical perspective. Annu Rev Control 2019;48:222-32.
  • [9] Cobelli C, Renard E, Kovatchev B. Artificial pancreas: Past, present, future. Diabetes 2011;60(11):2672-82.
  • [10] Doyle I, Huyett LM, Lee JB, Zisser HC, Dassau E. Closed-Loop artificial pancreas systems: Engineering the algorithms. Diabetes Care 2014;37(5):1191-7.
  • [11] Bergman R, Phillips L, Cobelli C. Physiologic evaluation of factors controlling glucose tolerance in man: Measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. J Clin Investig 1981;68(6):1456-1467.
  • [12] Belmon AP, Auxillia J. An adaptive technique based blood glucose con-trol in type-1 diabetes mellitus patients. Int J Numer Methods Biomed Eng 2020;36(8):e3371.
  • [13] Khan MW, Abid M, Khan AQ, Mustafa G. Controller design for a fractional-order nonlinear glucose-insulin system using feedback linearization. Trans Inst Meas Control 2020;42(13):2372-81.
  • [14] Nath A, Dey R. Observer-based nonlinear control design for glucose regulation in type 1 diabetic patients: An LMI approach. Biomed Signal Process Control 2019;47:7-15.
  • [15] Borri A, Cacace F, De Gaetano A, Germani A, Manes C, Palumbo P, Panunzi S, Pepe P. Luenberger-like observers for nonlinear time-delay systems with application to the artificial pancreas: The attainment of good performance. IEEE Control Syst Mag 2017;37(4):33-49.
  • [16] Beneyto A, Puig V, Bequette BW, Vehi J. A hybrid automata approach for monitoring the patient in the loop in artificial pancreas systems. Sensors 2021;21(21):7117.
  • [17] Di Ferdinando M, Di Gennaro S, Pepe P. On sontag’s formula for the sampled-data observer-based stabilization of nonlinear time-delay systems. Automatica 2023;153:111052.
  • [18] Saleem MU, Farman M, Ahmad M, Rizwan M. Control of an artificial human pancreas. Chinese J Phys 2017;55(6):2273-82.
  • [19] Birjandi SZ, Sani SKH, Pariz N. Insulin infusion rate control using information theoretic–based nonlinear model predictive control for type 1 diabetes patients. Trans Inst Meas Control 2023;45(5):815-27.
  • [20] Borri A, Palumbo P, Manes C, Panunzi S, Gaetano A. Sampled-data observer-based glucose control for the artificial pancreas. Acta Polytech Hung 2017;14:79-94.
  • [21] Targui B, Castro-Gomez J-F, Hernández-González O, Valencia-Palomo G, Guerrero-Sánchez M-E. Observer-based control for plasma glucose regulation in Biomed Eng 2024;40(7):e3826.
  • [22] Golestani F, Tavazoei MS. Delay-independent regulation of blood glucose for type-1 diabetes mellitus patients via an observer-based predictor feedback approach by considering quantization constraints. Eur J Control 2022;63:240-52.
  • [23] Nath A, Dey R. Robust observer based control for plasma glucose regulation in type 1 diabetes patient using attractive ellipsoid method. IET Syst Biology 2019;13(2):84-91.
  • [24] Rudin W. Principles of mathematical analysis. McGraw-Hill; 1976.
  • [25] Sepasi S, Kalat AA, Seyedabadi M. An adaptive back-stepping control for blood glucose regulation in type 1 diabetes. Biomed Signal Process Control 2021;66:102498.
  • [26] Drexler D, Sápi J, Kovács L. 𝐻∞ control of nonlinear system wtih positive input with application to antiagiogenic therapy. IFAC 2018;51-25:146-51.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-80df5c7f-a830-4fcc-8d60-b76ca8772964
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.