Simulation results for on-line optimization of a batch bioreactor using nonlinear filtering and optimal control

The computation of optimal control profiles for batch bioreactors is based on the use of simple and empirical dynamic models. Since these models present some level of uncertainty, the difference between the model dynamics and the reactor dynamics can have significant effects in the reliability of the calculated profile. To develop near optimal control trajectories considering this drawback, we propose to calculate successive control profiles on a moving time horizon using a mathematical model in which the kinetic parameters are estimated by an observer. The desired objective is to generate a near optimal control trajectory adapted to the “running” fermentation. This idea results in a nonlinear estimator plus an optimizer arrangement that so far has not been applied to batch fermentors. Numerical simulations are performed on xanthan-gum batch fermentations and reasonably good results are obtained.