On-line optimization control for a time-varying process using multiple models: A laboratory scale fermenter application

The aim of this work is to present a technique which is able to deal with discontinuous time varying systems based on the identification of local linear models at different operating conditions. The ideal process trajectory is predicted through an optimizing algorithm using a Model Predictive Control Scheme (MPC) in cascade with conventional PID controllers which are responsible for driving the system along at the optimal conditions. A laboratory scale reactor for the production of gluconic acid is studied in order to assess the reliability and performance of this control strategy.