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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

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

Ata de Conferência Internacional

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

Páginas: 213-218

21st Mediterranean Conference on Control and Automation (MED)

Platanias, GREECE, JUN 25-28, 2013

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 3 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6