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In the present work, we propose a generic dynamic analysis and model reduction framework for autothermal reactors. We document the existence of a two time scale dynamic behavior, and identify the variables that are associated with each time scale. We derive reduced-order, nonlinear models for the dynamics in each time scale. We show that the derived slow model corresponds to generally accepted empirically derived simplified models for the class of reactors considered. Subsequently, we present illustrative simulation results on a hydrogen production reactor.

Asymptotic behaviour of a two time scale stochastic approximation algorithm is analysed in terms of a related singular ordinary differential equation.

The nonlinear filtering problem for singularly perturbed or two time scale problems involves equations of high dimension and with high gains. It is desirable to simplify the filter by exploiting the multiple time scale property and do some sort of averaging of the “fast” dynamics. The problem is rather subtle. But it can be shown under broad conditions that the so-called averaged filter is nearly optimal for large scale separations.