Parameter identification of bacterial growth bioprocesses using particle swarm optimization

This paper deals with the off-line parameters identification for a class of bacterial growth bioprocesses using particle swarm optimization (PSO) techniques. Particle swarm optimization is a relatively new heuristic method that has produced promising results for solving complex optimization problems. In this paper one uses some variants of the PSO algorithm for parameter estimation of a complex biotechnological system. The identification problem is formulated as a multi-modal numerical optimization problem with high dimension. The performances of the method are analyzed by numerical simulations.