Kalman Filter Design for a Second-order Model of Anaerobic Digestion

The paper deals with the state estimation of a second-order model of anaerobic digestion. This estimation is necessary to implement the sophisticated control algorithms that have already been developed for this process. Hereby design and performance of a classical Kalman filter (compared with other two deterministic estimation approaches) for the main variables of this model have been discussed and analysed by simulations. The performance analysis has been conducted at realistic random perturbations, comparable with experimental data, on the one hand, and on the other – with and without parameter perturbations. Although at random perturbations alone the Kalman filter has a clear advantage over the two equipollent deterministic estimators, at the presence also of parameter perturbations, to which the Kalman filter is more sensitive, no such advantage is guaranteed.