Ergodicity Analysis and Antithetic Integral Control of a Class of Stochastic Reaction Networks with Delays

Abstract

Delays are important phenomena arising in a wide variety of real-world systems, including biological ones, because of diffusion/propagation effects or as simplifying modeling elements. We propose here to consider delayed stochastic reaction networks, a class of networks that has received little attention until now. We demonstrate here that by restricting the delays to be phase-type distributed, one can represent the associated delayed reaction network as a reaction network with finite-dimensional state-space. In particular, we prove, for mass-action unimolecular and certain bimolecular networks, that the delayed stochastic reaction network is ergodic if and only if the delay-free network is ergodic as well. These results demonstrate that delays cause little to no harm to the ergodicity property of reaction networks as long as the delays are phase-type distributed, and this holds regardless of the complexity of their distribution. We also prove that the presence of those delays adds convolution terms in the moment equation but does not change the value of the stationary means compared to the delay-free case. The covariance, however, is influenced by the presence of the delays. Finally, the control of a certain class of delayed stochastic reaction network using a delayed antithetic integral controller is considered. It is proven that this controller achieves its goal provided that the delay-free network satisfies the conditions of ergodicity and output-controllability.