We consider a stochastic model of the two-dimensional chemostat as a diffusion process for the concentration of substrate and the concentration of biomass. The model allows for the washout phenomenon: the disappearance of the biomass inside the chemostat. We establish the Fokker-Planck associated with this diffusion process, in particular we describe the boundary conditions that modelize the washout. We propose an adapted finite difference scheme for the approximation of the solution of the Fokker-Planck equation.
A chemostat is a fixed volume bioreactor in which micro-organisms are grown in a continuously renewed liquid medium. We propose a stochastic model for the evolution of the concentrations in the single species and single substrate case. It is obtained as a diffusion approximation of a pure jump Markov process, whose increments are comparable in mean with the deterministic model. A specific time scale, related to the noise intensity, is considered for each source of variation. The geometric structure of the problem, usable by identification procedures, is preserved both in the drift and diffusion term. We study the properties of this model by numerical experiments.
This paper proposes a (stochastic) Langevin-type formulation to modelize the continuous time evolution of the state of a biological reactor. We adapt the classical technique of asymptotic observer commonly used in the deterministic case, to design a Monte-Carlo procedure for the estimation of an unobserved reactant. We illustrate the relevance of this approach by numerical simulations.
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