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高水平学术前沿讲座
点击率:368 作者:中国科大自动化系 来源:http://auto.ustc.edu.cn 时间:2017-01-02 00:00:00
  

高水平学术前沿讲座

 

报告题目:Fractional order model reference adaptive control for anesthesia

报告时间:201714日下午3:00

报告地点:电二楼208会议室

报告人:     Yu Tang 教授

 报告人单位:墨西哥国立大学

选课链接:http://yjs.ustc.edu.cn/xsbg/

               

摘要: Control of anesthesia has been an active research for the past decades. Designing a controller for anesthesia faces a variety of challenges: inter and intra-patient variability, multivariable characteristics, variable time delays, dynamics dependent on the hypnotic agent and stability issues to just mention a few. 

Commonly, the mathematical model used to study the depth of anesthesia is a PK/PD (pharmacokinetic/pharmacodynamic) model, with a third-order linear PK model, and a PD model consisting of a first-order linear transfer function and a nonlinearity  (a Wiener structure). Despite its plausibility accepted by biomedical and control community, being a physiologically based empirical model it has many difficulties for controller designs.

Fractional order (FO) models are mathematical representation of a physical system with fractional differential equations. Fractional calculus is the generalization of the classical operation of derivation and integration to orders other than integer.

In this talk we consider the problem of designing a fractional order model reference adaptive controller (FO-MRAC). Towards this end, an FO modelfor anesthesia is first proposed, which is shown to be able to follow the anesthesia dynamics by identifying the PK/PD model. Then, based on this model a simple FO-MRAC is designed. The stability of the close-loop system is established employing Lyapunov analysis. Instrumental to the convergence of the control error to zero is an extension of the Barbalat Lemma for fractional order systems, whose proof is detailed in the talk.

 

个人简介: 唐煜教授于1988年在墨西哥国立大学获得电气工程博士学位,1991年获评墨西哥科学院最佳博士论文,获得Weizmann 奖,19941月到199512月任墨西哥电力研究院顾问,1995年获评墨西哥国立大学杰出青年学者,现为墨西哥科学院和SNI的正式会员,墨西哥国立大学一级教授。唐教授的研究方向包括自适应控制系统辨识、非线性控制及其在生物医学、工业中的应用。


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