对于非线性心肺系统的辐射基功能网络的倒退控制
Anake Pomprapa1, Marian Walter1, Steffen Leonhardt1
1Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.
IFAC-PapersOnLine
|April 15, 2024
概括
这项研究应用了后退控制来调节心肺系统的氧化,即使是未知的动态. 该方法使用辐射基功能网络来管理临界缺氧并改善患者的康复,包括那些患有SARS-CoV-2的患者.
科学领域:
- 生物医学工程 生物医学工程
- 控制系统工程 控制系统工程
- 计算生理学计算生理学
背景情况:
- 氧气治疗对于管理严重的缺氧和重症监护情况至关重要.
- 心肺系统表现出复杂的非线性动态和歇斯底里,这对精确的氧化控制构成了挑战.
- 精确的氧化调节对于患者的康复至关重要,特别是在严重的疾病中,例如由SARS-CoV-2引起的疾病.
研究的目的:
- 在非线性心肺系统模型中开发和验证一个逆向控制策略来调节氧化.
- 整合一个辐射基函数 (RBF) 网络,用于适应性识别未知的系统动态和hysteresis.
- 在模拟生理变化下证明拟议系统的稳定性和控制性能.
主要方法:
- 使用了一种非线性多隔间人类心肺系统模型,其hysteresis未知.
- 一个辐射基函数 (RBF) 网络被纳入了一个闭环子系统,用于自适应系统识别.
- 根据利亚普诺夫稳定定理设计了一个后退控制器来调节氧化.
主要成果:
- 后退控制器,加上RBF网络,有效地调节了模拟心肺系统中的氧化.
- 控制策略表现出强大的稳定性和性能,尽管存在未知的非线性和模拟的生理障碍.
- 模拟证实了控制器在模仿严重疾病的条件下有效管理氧化的能力,包括SARS-CoV-2.
结论:
- 后退控制与RBF基于网络的自适应识别相结合,为重症监护中的精确氧化管理提供了一个有希望的方法.
- 这种方法为复杂的心肺系统提供了稳定有效的控制解决方案,这些系统具有未建模的动态.
- 这些发现对改善氧化疗法和重症监护机构患者的治疗结果有重大影响,特别是在流行病期间.
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