Handling Parameter Variations during the Treatment of Type 1 Diabetes Mellitus: In Silico Results
Autor: | Maria Fernanda Villa Tamayo, Pablo S. Rivadeneira, Michelle A. Caicedo Alvarez |
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Rok vydání: | 2019 |
Předmět: |
0209 industrial biotechnology
Type 1 diabetes Article Subject lcsh:Mathematics General Mathematics In silico General Engineering 030209 endocrinology & metabolism 02 engineering and technology Hypoglycemia lcsh:QA1-939 Target range medicine.disease 03 medical and health sciences 020901 industrial engineering & automation 0302 clinical medicine Model parameter lcsh:TA1-2040 Control theory medicine Sensitivity (control systems) lcsh:Engineering (General). Civil engineering (General) Parametric statistics Mathematics |
Zdroj: | Mathematical Problems in Engineering, Vol 2019 (2019) |
ISSN: | 1563-5147 1024-123X |
DOI: | 10.1155/2019/2640405 |
Popis: | Type 1 diabetic patients need a strict treatment to regulate blood glucose concentration in a target range. Despite the development of different control strategies, the model parameter variations, given by physiological changes, can generate an inaccurate treatment and in consequence hyperglycemia and hypoglycemia episodes. Therefore, it is necessary to use control techniques that compensate such effects and maintain the control goals. Here, the effect of parametric variations is examined by the sensitivity analysis from which the most influential parameters in glycemia dynamics are detected. Based on that, an offset-free MPC strategy for impulsive systems is given for the first time in literature and simulated for type 1 diabetes treatment. This scheme along with the impulsive zone MPC with artificial variables reestablishes the normoglycemia behavior since the parameter variations are adequately rejected. However, only parametric variations up to 50% from their nominal values are well compensated, which suggests that more robust formulations are needed to ensure a greater rejection of physiological variations. |
Databáze: | OpenAIRE |
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