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Structural identifiability of the parameters of a nonlinear batch reactor model
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Abstract
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.
If it is possible to measure the initial concentration of growth-limiting substrate
as well, all model parameters are globally identifiable.