Extremum Seeking Control Based Zone Adaptation for Zone Model Predictive Control in Type 1 Diabetes * *This work is supported by the National Institutes of Health Grants DP3DK094331, DP3DK104057 and UC4DK108483
| Autor: | Ravi Gondhalekar, Zhixing Cao, Francis J. Doyle, Eyal Dassau |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
030209 endocrinology & metabolism 02 engineering and technology Upper and lower bounds 03 medical and health sciences Model predictive control 020901 industrial engineering & automation 0302 clinical medicine Control and Systems Engineering Control theory Robustness (computer science) Range (statistics) Blood sugar regulation Dither Glycemic Mathematics |
| Zdroj: | IFAC-PapersOnLine. 50:15074-15079 |
| ISSN: | 2405-8963 |
| Popis: | Clinical trials have demonstrated that zone model predictive control is an effective closed-loop blood glucose regulation method for people with type 1 diabetes (T1D). This paper presents a universal model-free optimization method to seek an optimal zone for T1D patients individually. A clinical glycemic risk index named relative regularized glycemic penalty index (rrGPI) is used as the cost function. The proposed method is based on extremum seeking control that uses only the rrGPI index, calculated from measurements by a continuous glucose monitor, to update a controller’s blood glucose target zone’s upper bound and lower bound simultaneously. The method proposed uses a decaying feedback gain and a vanishing dither signal to improve the extremum seeking controller’s robustness against various uncertainties. In silico trials suggest that the proposed method is able to converge to the personalized optimal zone in less than a week of adaptation. In a 30-day in silico trial, the time spent in the range [70,180] mg/dL is increased by about 3% and 2% for unannounced 60 gCHO (grams of carbohydrates) and 90 gCHO meals, respectively, compared to the zone [80,140] mg/dL employed in the authors’ current zone controller. |
| Databáze: | OpenAIRE |
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