Global-nonlinear stochastic estimation of exothermic reactors with temperature measurement

In this work, the problem of estimating the concentration of exothermic rectors with temperature measurement is addressed. The problem is treated within a global nonlinear stochastic framework, according to the Fokker Plank-based Kushner filtering theory. The on-line solution of the associated two-dimensional partial differential equation driven by the temperature measurements yields the evolution of the conditioned concentration-temperature probability density function (PDF), with considerable more information than the one provided by standard EKF based on a local-nonlinear approach. A catalytic reactor with deterministic multistability, experimental data, and previously addressed with EKF is addressed as case example, yielding: (i) the on-line evolution of the (possibly bimodal) conditioned concentration probability density function, and (ii) mean uncertainty values which are better than the ones drawn with EKF.