STRUCTURAL IDENTIFIABILITY OF THE PARAMETERS OF A NONLINEAR BATCH REACTOR MODEL

The similarity transformation approach is used to analyze the structural identifiability of the parameters of a nonlinear model of microbial growth in a batch reactor in which only the concentration of microorganisms is measured. It is found that some of the model parameters are unidentifiable from this experiment, thus providing the first example of a real-life nonlinear model that turns out not to be globally identifiable. It it is possible to measure the initial concentration of growth-limiting substrate as well, all model parameters are globally identifiable.