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In this work a modified multi-population genetic algorithm (MPGA) without the performance of the mutation operator is proposed. The idea is to reduce the convergence time and therefore to increase the identification procedure effectiveness for on-line application of the algorithm. Modified MPGA, classical multipopulation GA and two other modifications are tested for parameter identification problem of an E. coli non-linear fed-batch cultivation model. The contribution of each modification measure to the performance improvement is demonstrated. The obtained results show that the highest accuracy for parameter identification of the considered model is achieved with the multipopulation GA with Modification 1. The best calculation time is shown by the multipopulation GA without mutation.

A MODIFIED MULTI-POPULATION GENETIC ALGORITHM FOR PARAMETER IDENTIFICATION OF CULTIVATION PROCESS MODELS