Optimizing blood glucose regulation in type 1 diabetes: A fractional order controller approach
Source abstract
Abstract
This study presents the design and implementation of a Fractional Order Proportional, Integral, and Derivative (FOPID) controller intended for the regulation of blood glucose levels in individuals with type 1 diabetes mellitus (T1DM). The efficacy of this controller is evaluated through its application to a nonlinear Stolwijk–Hardy model simulating T1DM patients, accounting for a range of physiological conditions. Utilizing a genetic algorithm, the parameters of the FOPID controller are fine-tuned. By conducting a comparative analysis with previously established control algorithms, the performance of the proposed controller is validated, demonstrating its superior performance. The results underscore the significant improvements achieved by the proposed controller in maintaining blood glucose concentrations within safe thresholds, particularly in scenarios involving disruptions due to meals.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Control Systems Design · Diabetes Management and Research · Pancreatic function and diabetes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechatronics, Thiagarajar College of Engineering 1 , Madurai 625015, Tamil Nadu, India
Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering 2 , Nagpur, India
Department of Industrial Management, National Taiwan University of Science and Technology 3 , Taipei 106335, Taiwan
Department of Computer Science and Engineering, University of Tennessee at Chattanooga 4 , Chattanooga, Tennessee 37403, USA
Department of Environmental Health, Harvard T.H. Chan School of Public Health 5 , Boston, Massachusetts 02115, USA
Funding
USA National Academy of Medicine, AI Tennessee Initiative, and the support at the University of Tennessee at Chattanooga.
References (25)
Show source-provided references
1. Closed-loop control of blood glucose level in type-1 diabetics: A simulation study
2. Simulation study on closed loop control algorithm of type 1 diabetes mellitus patients10.4103/0377-2063.57601 ↗
3. Comparison of control algorithms for the blood glucose concentration in a virtual patient with an artificial pancreas10.1016/j.cherd.2011.10.017 ↗
4. Presentation of the model and optimal control of non-linear fractional-order chaotic system of glucose–insulin10.1080/10255842.2023.2205979 ↗
5. A fractional-order control model for diabetes with restraining and time-delay10.1007/s12190-023-01885-5 ↗
6. Real-time application of IMC-PID-FO multi-loop controllers on the coupled tanks process10.1177/0959651820983062 ↗
7. Design and implementation of model predictive controller for type-I diabetics10.1504/ijbet.2011.041778 ↗
8. Design of switched model predictive control algorithms for a dual-hormone artificial pancreas10.1016/j.ifacol.2018.11.647 ↗
9. Super twisting sliding mode control algorithm for developing artificial pancreas in type 1 diabetes patients10.1016/j.bspc.2017.06.009 ↗
10. Adaptive continuous-time model predictive controller for implantable insulin delivery system in Type I diabetic patient10.1002/oca.2250 ↗
11. An automatic insulin infusion system based on LQG control technique10.1504/ijbet.2015.068109 ↗
12. Design of backstepping LQG controller for blood glucose regulation in type I diabetes patient10.1504/ijaac.2020.108276 ↗
13. Challenges and recent progress in the development of a closed-loop artificial pancreas10.1016/j.arcontrol.2012.09.007 ↗
14. Blood glucose control by a model predictive control algorithm with variable sampling rate versus a routine glucose management protocol in cardiac surgery patients: A randomized controlled trial10.1210/jc.2007-0434 ↗
15. A review on control-relevant glucose-insulin dynamics models and regulation strategies10.1177/0959651819870328 ↗
16. Wiener model-based CDM-PI controller for pH neutralisation process10.1504/ijmic.2015.071889 ↗
17. Robust adaptive fractional order proportional integral derivative controller design for uncertain fractional order nonlinear systems using sliding mode control10.1177/0959651818758209 ↗
18. Particle swarm optimization technique for speed control and torque ripple minimization of switched reluctance motor using PID and FOPID controllers10.1007/s41870-023-01656-2 ↗
19. Fractional-order PID controller design using PSO and GA
20. Enhancing the transient stability of interconnected power systems by designing an adaptive fuzzy-based fractional order PID controller10.1016/j.egyr.2023.11.058 ↗
21. An intelligent optimized fractional order sliding mode controller for biological system10.1007/s11042-024-18194-z ↗
22. Comparison of PID-based control algorithms for daily blood glucose control
23. A. S. Basher , “Design fuzzy control system for blood glucose level for type-I diabetes mellitus patients using GA: A simulation study,” M.S. thesis, The Islamic University of Gaza, 2017.
24. Control of blood glucose concentration in type I diabetic patients
25. Design of a genetic-algorithm-based self-tuning sliding fuzzy controller for an active suspension system10.1177/2041304110394535 ↗