An observer for mass-action chemical reaction networks.

In biological research, experimental data analysis plays an important role since it enables quantitative understanding of biochemical processes. On the other hand, today's measurement techniques, in continuous development, generally allow measuring a subset of the major system's variables. Such major issue can be tackled by relying on a system's and mathematical approach. For instance, first principles modelling of metabolic or signal transduction networks typically leads to a set of nonlinear differential equations. In this paper we devise a nonlinear observer specifically suited for models of biochemical reaction networks. We show that the observer is locally convergent under certain observability conditions which can be inferred by elementary network analysis. The applicability and performance of the outlined observer are shown considering the state estimation problem for a benchmark biochemical reaction network.