2018
DOI: 10.1007/s11517-018-1872-6
|View full text |Cite
|
Sign up to set email alerts
|

Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system

Abstract: Artificial pancreas system (APS) is a viable option to treat diabetic patients. Researchers, however, have not conclusively determined the best control method for APS. Due to intra-/inter-variability of insulin absorption and action, an individualized algorithm is required to control blood glucose level (BGL) for each patient. To this end, we developed model predictive control (MPC) based on artificial neural networks (ANNs), which combines ANN for BGL prediction based on inputs and MPC for BGL control based o… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
15
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 35 publications
(15 citation statements)
references
References 35 publications
0
15
0
Order By: Relevance
“…Mathematical description of IL-2 therapy After intravenous administration of a drug, instantaneous jumps are observed in the drug concentration in plasma and target organ (22). In the framework of mathematical modeling, systems with discontinuities in their dynamics can be categorized as impulsive systems and allows for application of control engineering design tools (19,20,(23)(24)(25)(26)(27)(28)(29)(30)(31). Among these methods, model predictive control (MPC) techniques have been widely used (19,20,(23)(24)(25)(26)(27)(28) due to their ability to consider systemic constraints, which confine the dynamics of the system variables or the external control input.…”
Section: Methodsmentioning
confidence: 99%
“…Mathematical description of IL-2 therapy After intravenous administration of a drug, instantaneous jumps are observed in the drug concentration in plasma and target organ (22). In the framework of mathematical modeling, systems with discontinuities in their dynamics can be categorized as impulsive systems and allows for application of control engineering design tools (19,20,(23)(24)(25)(26)(27)(28)(29)(30)(31). Among these methods, model predictive control (MPC) techniques have been widely used (19,20,(23)(24)(25)(26)(27)(28) due to their ability to consider systemic constraints, which confine the dynamics of the system variables or the external control input.…”
Section: Methodsmentioning
confidence: 99%
“…Bahremand et al 28 have predicted blood glucose level (BGL) followed with the combination of artificial neural networks (ANNs) to a model predictive control (MPC). At first, the individual virtual subjects for diabetic rats were obtained through developing a mathematical model that suits better the data obtained based on food intake, insulin injection, and BGL data.…”
Section: Recent Research Work: An Overviewmentioning
confidence: 99%
“…After intravenous administration of a drug, instantaneous jumps are observed in the drug concentration in plasma and the target organ (Yang, 2001 iScience Article discontinuities in their dynamics can be categorized as impulsive systems and allow for application of control engineering design tools (Sopasakis et al, 2015;Rivadeneira et al, 2015Rivadeneira et al, , 2016Rivadeneira et al, , 2017Gonzá lez et al, 2017;Fontes and Pereira, 2012;Magni et al, 2007;Bahremand et al, 2019;Montaseri et al, 2018Montaseri et al, , 2020Rivadeneira and Moog, 2012). Among these methods, model predictive control (MPC) techniques have been widely used (Sopasakis et al, 2015;Rivadeneira et al, 2015Rivadeneira et al, , 2016Rivadeneira et al, , 2017Gonzá lez et al, 2017;Fontes and Pereira, 2012;Magni et al, 2007;Bahremand et al, 2019) due to their ability to consider systemic constraints, which confine the dynamics of the system variables or the external control input. In the context of pharmacodynamics, the control input is the administered drug.…”
Section: Mathematical Description Of Il-2 Therapymentioning
confidence: 99%