Identification techniques based on heuristic optimization for propagation processes

A metaheuristic is a general algorithmic framework which can be applied to different optimization problems with relative few modifications to make them adapted to a specific problem. This work describes a dynamic mathematical model for a bioprocess, which takes place into a Continuous Stirred Tank Bioreactor with delay in the recycle stream, containing four unknown parameters, which were calibrated using particle swarm optimization through the minimization of an evaluation function. Two kinetic expressions, the Monod and Haldane equations, commonly employed to describe microbial growth were tested in the model simulations. The identification problem is formulated as a multi-modal numerical optimization problem with high dimension. The performances of the identification methods are analyzed by numerical simulations.