Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jprocont.2009.06.003
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dc.titleA comparative study of three advanced controllers for the regulation of hypnosis
dc.contributor.authorYelneedi, S.
dc.contributor.authorLakshminarayanan, S.
dc.contributor.authorRangaiah, G.P.
dc.date.accessioned2014-06-16T09:24:50Z
dc.date.available2014-06-16T09:24:50Z
dc.date.issued2009-10
dc.identifier.citationYelneedi, S., Lakshminarayanan, S., Rangaiah, G.P. (2009-10). A comparative study of three advanced controllers for the regulation of hypnosis. Journal of Process Control 19 (9) : 1458-1469. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jprocont.2009.06.003
dc.identifier.issn09591524
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53982
dc.description.abstractThe anesthetic state is a dynamic combination of hypnosis, analgesia and neuromuscular blockade that is maintained by infusing a cocktail of drugs. This work focuses on controlling the hypnosis during a surgical procedure by automatic regulation of isoflurane and employs Bispectral Index (BIS) as the primary controlled variable. A seventh-order nonlinear pharmacokinetic-pharmacodynamic representation has been used for the hypnosis dynamics of patients. This study uses a model predictive control structure for the regulation of BIS. Performance of this controller has been tested for a range of patients and compared with two previously employed control strategies (cascade internal model controller and cascade controller with modeling error compensation). Performance of the three controllers has also been studied for a step change in BIS, measured disturbances and noise in the measured variables. Numerical simulations show that the model predictive controller performed better than the other two controllers. © 2009 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.jprocont.2009.06.003
dc.sourceScopus
dc.subjectBispectral Index
dc.subjectHypnosis control
dc.subjectModel predictive control
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.description.doi10.1016/j.jprocont.2009.06.003
dc.description.sourcetitleJournal of Process Control
dc.description.volume19
dc.description.issue9
dc.description.page1458-1469
dc.description.codenJPCOE
dc.identifier.isiut000271529200005
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