Endogenous model state and parameter estimation from an extensive batch experiment

In this paper an extensive batch experiment of endogenous process behavior in an aerobic biodegradation process is presented. From these experimental data, comprising measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, in a first step the states and unknown parameters in a four-compartmental model are reconstructed analytically. Subsequently, for a selected set of states and parameters, using the results of the previous step, a recursive state estimation procedure, in particular an Extended Kalman filter-based observer, is applied to deal with the noise properties of the data appropriately. From this it appears that the initially proposed model structure, and especially the hydrolysis term, has to be modifie