Absolutely robust controllers for chemical reaction networks
Absolutely robust controllers for chemical reaction networks
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DOI：
10.1098/rsif.2020.0031
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发表时间：
2020-05-27
影响因子：
3.9
通讯作者：
Enciso, German
中科院分区：
文献类型：
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作者：
Kim, Jinsu;Enciso, German
在这项工作中，我们设计了一种类型的控制器，包括添加一组特定的反应到现有的质量作用化学反应网络，以控制目标物种。这组反应对确定性网络和随机网络都有效，在后一种情况下，控制目标物种的均值和方差。我们采用了一种称为绝对浓度鲁棒性（ACR）的网络属性。我们提供的应用程序控制的多位点磷酸化模型以及受体配体信号系统。在这个框架中，我们使用了化学反应网络理论中的亏零定理以及多尺度模型降阶方法。我们表明，目标物种具有近似泊松分布与期望的平均值。我们进一步表明，ACR控制器可以带来强大的完美适应的目标物种，并补充最近推出的对偶反馈控制器用于随机化学反应。
In this work, we design a type of controller that consists of adding a specific set of reactions to an existing mass-action chemical reaction network in order to control a target species. This set of reactions is effective for both deterministic and stochastic networks, in the latter case controlling the mean as well as the variance of the target species. We employ a type of network property called absolute concentration robustness (ACR). We provide applications to the control of a multisite phosphorylation model as well as a receptor-ligand signalling system. For this framework, we use the so-called deficiency zero theorem from chemical reaction network theory as well as multiscaling model reduction methods. We show that the target species has approximately Poisson distribution with the desired mean. We further show that ACR controllers can bring robust perfect adaptation to a target species and are complementary to a recently introduced antithetic feedback controller used for stochastic chemical reactions.