Page 319 - Glucose Monitoring Devices
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326 CHAPTER 15 Automated closed-loop insulin delivery
[60] Turksoy K, Bayrak ES, Quinn L, Littlejohn E, Cinar A. Guaranteed stability of recur-
sive multi-input-single-output time series models. In: Proc. 2013 American control
conf. IEEE, Washington, DC; 2013. p. 77e82.
[61] Hajizadeh I, et al. Multivariable recursive subspace identification with application to
artificial pancreas systems. IFAC-PapersOnLine 2017;50(1):886e91.
[62] Van Overschee P, De Moor B. Subspace identification for linear systems: theory, imple-
mentation Methods. Springer; 1996.
[63] Wang Y, Gao F, Doyle FJ. Survey on iterative learning control, repetitive control, and
run-to-run control. Journal of Process Control 2009;19(10):1589e600.
[64] Owens C, Zisser H, Jovanovic L, Srinivasan B, Bonvin D, Doyle III FJ. Run-to-run con-
trol of blood glucose concentrations for people with type 1 diabetes mellitus. IEEE
Transactions on Biomedical Engineering 2006;53(6):996e1005.
[65] Magni L, et al. Run-to-run tuning of model predictive control for type 1 diabetes sub-
jects: in silico trial. Journal of Diabetes Science and Technology 2009;3(5):1091e8.
[66] Palerm CC, Zisser H, Jovanovi c L, Doyle FJ. A run-to-run control strategy to adjust
basal insulin infusion rates in type 1 diabetes. Journal of Process Control 2008;18(3):
258e65.
[67] Wang Y, Dassau E, Doyle IIIFJ. Closed-loop control of artificial pancreatic $b$ -cell in
type 1 diabetes mellitus using model predictive iterative learning control. IEEE Trans-
actions on Biomedical Engineering Feb. 2010;57(2):211e9.