Speaker
Description
Column liquid chromatography plays a vital role in the so-called downstream processing of biopharmaceuticals, where the goal is to extract and purify certain proteins from a mixture. Our goal is to employ a model-based approach for process optimization to improve the yield and purity of the product, while also achieving further economical and ecological benefits, e.g., due to an economical use of buffer components. Rate models in combination with suitable reaction schemes that model the specific adsorption process are often employed to describe chromatographic processes. The optimal control problems (OCPs) we are going to set up are hence governed by advection-diffusion-reaction-type partial differential equations (PDEs) with typically highly nonlinear reaction terms. Furthermore, since at least one flow reversal is often performed in practical applications to obtain sharper elution profiles, we are facing switching dynamics. Lastly, it is important to determine robust solutions in order to safeguard against, e.g., uncertain model parameters, such as reaction rates and feed composition. In this talk we present several strategies towards robustly optimal switching control applied to chromatographic separation processes. We discuss the obtained results, focusing on the quality of the product and how reversing the flow direction may play a role in terms of robustness.
