2018
DOI: 10.1016/j.bspc.2017.12.002
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Evaluation of an artificial pancreas in in silico patients with online-tuned internal model control

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Cited by 13 publications
(21 citation statements)
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“…In future, the performance of the multi-objective controller with proper exercise and activity model may be studied on in silico patients. Table 6 Meal time and sizes as given in [23] 24 h 3:00 am 3 two 75 gm at 7:00 am and 1:00 pm. One 50 gm at 8:00 pm.…”
Section: Resultsmentioning
confidence: 99%
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“…In future, the performance of the multi-objective controller with proper exercise and activity model may be studied on in silico patients. Table 6 Meal time and sizes as given in [23] 24 h 3:00 am 3 two 75 gm at 7:00 am and 1:00 pm. One 50 gm at 8:00 pm.…”
Section: Resultsmentioning
confidence: 99%
“…• Thus the proposed controller gives better performance with lesser hyperglycaemic and hypoglycaemic events and with a lesser amount of insulin infusion without using SM and IFL. Table 5 Comparison of controller responses with meal protocols and controller strategies [19] Controller performance Protocol #1 Protocol #2 As reported in [19] postprandial (PP) As reported in [19] overall (O) Proposed controller As reported in [19] postprandial (PP) As reported in [19] • Case 2: The performance of the proposed controller is also compared with the performance of fully-automated offline-and online tuned IMC and semi-automated online-tuned IMC [23]. The patient was subjected to the same meal disturbances as in scenario 1 [23] and is given in Table 6.…”
Section: Performance Comparison With Other Controllers From Earlier Rmentioning
confidence: 99%
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“…Large variants of control techniques exist for the control of blood glucose of T1DM patients for different patient models. Some of the relevant literature review is presented here, proportional integral derivative, 13 model predictive control, 27,28 fuzzy logic control, 29 adaptive control, 9,[30][31][32] and so on. These control techniques have been successfully and extensively implemented for the considered problem without addressing intrapatient variability issue explicitly in the controller design.…”
Section: Introductionmentioning
confidence: 99%