Multiparametric Model Predictive Control and State Estimation of the Hypnotic Component in Anesthesia Conference Paper

abstract

• 2016 IEEE. This paper describes multiparametric model predictive control strategies for the control of depth of anaesthesia. Based on a detailed compartmental model featuring a pharmacokinetic and a pharmacodynamics part, two different control strategies are employed: A nominal multiparametric model predictive control and a simultaneous multiparametric moving horizon estimation and model predictive control. The control strategies are tested on a set of 12 patients in the induction and maintenance phase and analyzed comparatively. Moreover the inter-As well as the intra-patient variability is analyzed in detail. The performed simulations show good performances and satisfactory behavior.

name of conference

• 2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

authors

• Pistikopoulos, Stratos

published proceedings

• 2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

author list (cited authors)

• Nacu, I., & Pistikopoulos, E. N.

citation count

• 1

complete list of authors

• Naşcu, Ioana||Pistikopoulos, Efstratios N

publication date

• May 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Bioengineering
• Clinical Research

Digital Object Identifier (DOI)

• 10.1109/aqtr.2016.7501357

International Standard Book Number (ISBN) 13

• 9781467386906

start page

• 1

end page

• 6

URL

• http://dx.doi.org/10.1109/aqtr.2016.7501357