J. A. Méndez, J. Reboso, Santiago Torres Álvarez, Hector Reboso
{"title":"静脉麻醉控制的预测算法","authors":"J. A. Méndez, J. Reboso, Santiago Torres Álvarez, Hector Reboso","doi":"10.1109/ICCA.2010.5524313","DOIUrl":null,"url":null,"abstract":"This work deals with anesthesia control in humans. The control problem is to regulate the hypnosis state of the patient around a target specified by the anesthetist. The drug used here is propofol and the controller will work in general anesthesia conditions. As a preliminary study, real-time results with PI control are presented to demonstrate the limitations of this strategy. As an alternative, this paper introduces a model based predictive control to regulate the hypnosis depth. The basis of the algorithm is to combine two terms to compute the control law. One is obtained from the inverse dynamics of the patient and the other is obtained from a predictive controller that corrects the deviations of the controlled variable. The goal is to show the applicability of the proposed strategy and to demonstrate the increase in performance when compared to signal based controllers. The paper presents For this, real and simulated results are presented in the paper.","PeriodicalId":155562,"journal":{"name":"IEEE ICCA 2010","volume":"212 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive algorithm for intravenous anesthesia control\",\"authors\":\"J. A. Méndez, J. Reboso, Santiago Torres Álvarez, Hector Reboso\",\"doi\":\"10.1109/ICCA.2010.5524313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work deals with anesthesia control in humans. The control problem is to regulate the hypnosis state of the patient around a target specified by the anesthetist. The drug used here is propofol and the controller will work in general anesthesia conditions. As a preliminary study, real-time results with PI control are presented to demonstrate the limitations of this strategy. As an alternative, this paper introduces a model based predictive control to regulate the hypnosis depth. The basis of the algorithm is to combine two terms to compute the control law. One is obtained from the inverse dynamics of the patient and the other is obtained from a predictive controller that corrects the deviations of the controlled variable. The goal is to show the applicability of the proposed strategy and to demonstrate the increase in performance when compared to signal based controllers. The paper presents For this, real and simulated results are presented in the paper.\",\"PeriodicalId\":155562,\"journal\":{\"name\":\"IEEE ICCA 2010\",\"volume\":\"212 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE ICCA 2010\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2010.5524313\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE ICCA 2010","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2010.5524313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive algorithm for intravenous anesthesia control
This work deals with anesthesia control in humans. The control problem is to regulate the hypnosis state of the patient around a target specified by the anesthetist. The drug used here is propofol and the controller will work in general anesthesia conditions. As a preliminary study, real-time results with PI control are presented to demonstrate the limitations of this strategy. As an alternative, this paper introduces a model based predictive control to regulate the hypnosis depth. The basis of the algorithm is to combine two terms to compute the control law. One is obtained from the inverse dynamics of the patient and the other is obtained from a predictive controller that corrects the deviations of the controlled variable. The goal is to show the applicability of the proposed strategy and to demonstrate the increase in performance when compared to signal based controllers. The paper presents For this, real and simulated results are presented in the paper.