Design of Depth of Anesthesia Controllers in the Presence of Model Uncertainty

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Daniela V Caiado (Author) Other; Joao M Lemos (Author) Other; Bertinho A Costa (Author) Other; Margarida M Silva (Author) Other; Teresa F Mendonca (Author) FCUP

Conference proceedings International

Title: 2013 21ST MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED)

Pages: 213-218

21st Mediterranean Conference on Control and Automation (MED)

Platanias, GREECE, JUN 25-28, 2013

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-008-EXK

DOI: 10.1109/med.2013.6608724

Abstract (EN): A major obstacle in the design of controllers to regulate the depth of anesthesia (DoA) consists in the high model uncertainty due to inter-patient variability. Surprisingly, the use of control design methods that explicitly tackle this problem is almost absent from the literature on automatic control of anesthesia. In this work, a DoA controller is designed taking into account model uncertainty to comply with robust stability and robust performance specifications for a patient population undergoing elective general surgery, with hypnosis induced by the drug propofol. Due to its Wiener nonlinear structure, the DoA model can be linearized around a given operating point. Therefore, using a database with 18 patient models, a non-parametric description of uncertainty for a linearized model is first performed. By using H-infinity design methods, a continuous linear controller is then designed so as to ensure robust stability and performance within the uncertainty bounds defined. The controller that results from this procedure is approximated by a controller with a lower order that, in turn, is redesigned in discrete time for computer control application. The final result is tested in nonlinear realistic patient models, with acceptable closed-loop results.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6