{"title":"数学生物学","authors":"F. Hoppensteadt","doi":"10.4249/scholarpedia.2877","DOIUrl":null,"url":null,"abstract":"This paper considers a model of the human cardiovascular-respiratory control system with one and two transport delays in the state equations describing the respiratory system. The effectiveness of the control of the ventilation rate V̇A is influenced by such transport delays because blood gases must be transported a physical distance from the lungs to the sensory sites where these gases are measured. The short term cardiovascular control system does not involve such transport delays although delays do arise in other contexts such as the baroreflex loop (see [46]) for example. This baroreflex delay is not considered here. The interaction between heart rate, blood pressure, cardiac output, and blood vessel resistance is quite complex and given the limited knowledge available of this interaction, we will model the cardiovascular control mechanism via an optimal control derived from control theory. This control will be stabilizing and is a reasonable approach based on mathematical considerations as well as being further motivated by the observation that many physiologists cite optimization as a potential influence in the evolution of biological systems (see, e.g., Kenner [29] or Swan [62]). In this paper we adapt a model, previously considered (Timischl [63] and Timischl et al. [64]), to include the effects of one and two transport delays. We will first implement an optimal control for the combined cardiovascular-respiratory model with one state space delay. We will then consider the effects of a second delay in the state space by modeling the respiratory control via an empirical formula with delay while the the complex relationships in the cardiovascular control will still be modeled by optimal control. This second transport delay associated with the sensory system of the respiratory control plays an important role in respiratory stability. As an application of this model we will consider congestive heart failure where this transport delay is larger than normal and the transition from the quiet awake state to stage 4 (NREM) sleep. The model can be used to study the interaction between cardiovascular and respiratory function in various situations as well as to consider the influence of optimal function in physiological control system performance. J.J. Batzel: SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 22, 8010 Graz, Austria. e-mail: jerry.batzel@uni-graz.at F. Kappel: Institute for Mathematics and Scientific Computing and SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 36, 8010 Graz, Austria. e-mail: franz.kappel@uni-graz.at S. Timischl-Teschl: Fachhochschule Technikum Wien, Hoechstaedplatz 5, 1200 Vienna, Austria. e-mail: susanne.teschl@technikum-wien.at Supported by FWF (Austria) under grant F310 as a subproject of the Special Research Center F003 “Optimization and Control” Mathematics Subject Classification (2000): 92C30, 49J15","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"52 1","pages":"2877"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mathematical biology\",\"authors\":\"F. 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The interaction between heart rate, blood pressure, cardiac output, and blood vessel resistance is quite complex and given the limited knowledge available of this interaction, we will model the cardiovascular control mechanism via an optimal control derived from control theory. This control will be stabilizing and is a reasonable approach based on mathematical considerations as well as being further motivated by the observation that many physiologists cite optimization as a potential influence in the evolution of biological systems (see, e.g., Kenner [29] or Swan [62]). In this paper we adapt a model, previously considered (Timischl [63] and Timischl et al. [64]), to include the effects of one and two transport delays. We will first implement an optimal control for the combined cardiovascular-respiratory model with one state space delay. 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引用次数: 0
摘要
本文考虑了在描述呼吸系统的状态方程中具有一个和两个传输延迟的人体心血管-呼吸控制系统模型。由于血气必须从肺部运输一段物理距离到测量这些气体的感觉部位,因此这种运输延迟影响了控制通气量V (A)的有效性。短期心血管控制系统不涉及这种传输延迟,尽管延迟确实出现在其他情况下,例如气压反射回路(见[46])。这里不考虑气压反射延迟。心率、血压、心输出量和血管阻力之间的相互作用非常复杂,鉴于这种相互作用的知识有限,我们将通过从控制理论推导出的最优控制来模拟心血管控制机制。这种控制将是稳定的,是一种基于数学考虑的合理方法,也是许多生理学家将优化作为生物系统进化的潜在影响的观察结果所进一步激发的(例如,参见Kenner bbb或Swan[62])。在本文中,我们调整了先前考虑的模型(Timischl[63]和Timischl等人[64]),以包括一次和两次运输延迟的影响。我们将首先实现具有一个状态空间延迟的心血管-呼吸组合模型的最优控制。然后,我们将考虑第二次延迟在状态空间中的影响,通过一个带有延迟的经验公式来建模呼吸控制,而心血管控制中的复杂关系仍将通过最优控制来建模。这种与呼吸控制感觉系统有关的第二次转运延迟在呼吸稳定中起着重要作用。作为该模型的应用,我们将考虑充血性心力衰竭,其中这种转运延迟比正常情况大,并从安静的清醒状态过渡到第4阶段(NREM)睡眠。该模型可用于研究各种情况下心血管和呼吸功能之间的相互作用,并考虑最优功能对生理控制系统性能的影响。J.J. Batzel: SFB“Optimierung und controlle”,Karl-Franzens-Universität, Heinrichstraße 22, 8010 Graz,奥地利。e-mail: jerry.batzel@uni-graz.at F. Kappel:数学和科学计算研究所和SFB“Optimierung und Kontrolle”,Karl-Franzens-Universität, Heinrichstraße 36, 8010 Graz,奥地利。S. Timischl-Teschl:维也纳理工学院,奥地利维也纳,Hoechstaedplatz 5, 1200。e-mail: susanne.teschl@technikum-wien.at由奥地利FWF (Austria)资助,F310专项研究中心F003“优化与控制”数学学科分类(2000):92C30, 49J15
This paper considers a model of the human cardiovascular-respiratory control system with one and two transport delays in the state equations describing the respiratory system. The effectiveness of the control of the ventilation rate V̇A is influenced by such transport delays because blood gases must be transported a physical distance from the lungs to the sensory sites where these gases are measured. The short term cardiovascular control system does not involve such transport delays although delays do arise in other contexts such as the baroreflex loop (see [46]) for example. This baroreflex delay is not considered here. The interaction between heart rate, blood pressure, cardiac output, and blood vessel resistance is quite complex and given the limited knowledge available of this interaction, we will model the cardiovascular control mechanism via an optimal control derived from control theory. This control will be stabilizing and is a reasonable approach based on mathematical considerations as well as being further motivated by the observation that many physiologists cite optimization as a potential influence in the evolution of biological systems (see, e.g., Kenner [29] or Swan [62]). In this paper we adapt a model, previously considered (Timischl [63] and Timischl et al. [64]), to include the effects of one and two transport delays. We will first implement an optimal control for the combined cardiovascular-respiratory model with one state space delay. We will then consider the effects of a second delay in the state space by modeling the respiratory control via an empirical formula with delay while the the complex relationships in the cardiovascular control will still be modeled by optimal control. This second transport delay associated with the sensory system of the respiratory control plays an important role in respiratory stability. As an application of this model we will consider congestive heart failure where this transport delay is larger than normal and the transition from the quiet awake state to stage 4 (NREM) sleep. The model can be used to study the interaction between cardiovascular and respiratory function in various situations as well as to consider the influence of optimal function in physiological control system performance. J.J. Batzel: SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 22, 8010 Graz, Austria. e-mail: jerry.batzel@uni-graz.at F. Kappel: Institute for Mathematics and Scientific Computing and SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 36, 8010 Graz, Austria. e-mail: franz.kappel@uni-graz.at S. Timischl-Teschl: Fachhochschule Technikum Wien, Hoechstaedplatz 5, 1200 Vienna, Austria. e-mail: susanne.teschl@technikum-wien.at Supported by FWF (Austria) under grant F310 as a subproject of the Special Research Center F003 “Optimization and Control” Mathematics Subject Classification (2000): 92C30, 49J15