Traditionally, fed-batch biochemical process optimization and control use complicated models and off-line optimizers with no on-line model adaptation and re-optimization. This work demonstrates the applicability, effectiveness, and economic potential, of a simple phenomenological model for modeling, and a novel optimizer for on-line re-optimization and control of an aerobic fed-batch fermenter.