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AuthorPadmanabhan R.
AuthorMeskin N.
AuthorHaddad W.M.
Available date2020-04-16T06:56:49Z
Publication Date2019
Publication NameMathematical Biosciences
ResourceScopus
ISSN255564
URIhttp://dx.doi.org/10.1016/j.mbs.2019.01.012
URIhttp://hdl.handle.net/10576/14261
AbstractIn this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, we use the common anesthetic drug propofol used in intensive care units (ICUs). The proposed online integral reinforcement learning (IRL) algorithm is designed to provide optimal drug dosing for a given performance measure that iteratively updates the control solution with respect to the pharmacology of the patient while guaranteeing convergence to the optimal solution. Numerical results are presented using 10 simulated patients that demonstrate the efficacy of the proposed IRL-based controller.
SponsorThis publication was made possible by the GSRA grant no. GSRA1-1-1128-13016 from the Qatar National Research Fund (a member of the Qatar Foundation).
Languageen
PublisherElsevier Inc.
SubjectAnesthesia administration
Drug dosing
Optimal adaptive control
Reinforcement learning
TitleOptimal adaptive control of drug dosing using integral reinforcement learning
TypeArticle
Pagination131-142
Volume Number309


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