Purpose

Accurately reproducing physiological and time-varying variables in cardiac bioreactors is a difficult task for conventional control methods. This paper presents a new controller based on a genetic algorithm for the control of a cardiac bioreactor dedicated to the study and conditioning of heart valve substitutes.

Methods

A multi-objective genetic algorithm was designed to obtain an accurate simultaneous reproduction of physiological periodic time functions of the three most relevant variables characterizing the blood flow in the aortic valve. These three controlled variables are the flow rate and the pressures upstream and downstream of the aortic valve.

Results

Experimental results obtained with this new algorithm showed an accurate dynamic reproduction of these three controlled variables. Moreover, the controller can react and adapt continuously to changes happening over time in the cardiac bioreactor, which is a major advantage when working with living biological valve substitutes.

Conclusion

The strong non-linear interaction that exists between the three controlled variables makes it difficult to obtain a precise control of any of these, let alone all three simultaneously. However, the results showed that this new control algorithm can efficiently overcome such difficulties. In the particular field of bioreactors reproducing the cardiovascular environment, such a flexible, versatile and accurate reproduction of these three interdependent controlled variables is unprecedented.

中文翻译：

---

一种基于多目标进化算法的精确控制心脏生物反应器流速和血压的新方法。

目的

对于常规控制方法而言，在心脏生物反应器中准确再现生理和时变变量是一项艰巨的任务。本文提出了一种基于遗传算法的新型控制器，用于控制心脏生物反应器，致力于心脏瓣膜替代物的研究和调节。

方法

设计了一种多目标遗传算法，以准确同步地再现表征主动脉瓣血流的三个最相关变量的生理周期时间函数。这三个控制变量是主动脉瓣上游和下游的流速和压力。

结果

用这种新算法获得的实验结果显示出这三个控制变量的精确动态再现。而且，控制器可以对心脏生物反应器中随时间发生的变化做出连续的反应和适应，这在使用活体生物瓣膜替代品时是一个主要优势。

结论

这三个控制变量之间存在很强的非线性相互作用，因此很难对其中任何一个进行精确控制，更不用说同时对三个变量进行精确控制了。然而，结果表明，这种新的控制算法可以有效地克服这些困难。在再现心血管环境的生物反应器的特定领域中，这三个相互依赖的受控变量的这种灵活，通用和准确的再现是前所未有的。