This paper presents the implementation of functional state approach to modelling of Escherichia coli fed-batch cultivation. Due to the complex metabolic pathways of microorganisms, the accurate modelling of bioprocesses is rather difficult. The functional state approach of a process is an alternative concept which helps in modelling and control of complex processes. The approach main idea is developing of models based on multiple submodels for each functional states (operating regime). In each functional state the process is described by a conventional type of model, called the local model, which is valid in this state. For parameter identification of the model the genetic algorithms are used. Genetic algorithms are directed random search techniques, applying the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search spaces. Based on the available experimental data and simulations of E. coli fed-batch cultivation it is shown how this process can be divided into functional states and how the model parameters can be obtained on the basis of genetic algorithms. By simulation and comparison between the results and experimental data, can be seen how the concept of functional state approach works and how effective is the proposed identification scheme.

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