Online & Offline Optimal Control of Chemical and Biotechnological Processes

Challenges

Bringing academia and industry together to apply offline and online optimal control to dynamic processes in Chemistry and Biotechnology presents several hurdles. Differences in practical needs and theoretical approaches can make collaboration difficult. Developing new algorithms and software demands a better understanding of how models are built, reduced, and controlled, which is often complex and resource-intensive. There’s also a lack of standardized workflows, making it harder to apply solutions consistently. Planning future efforts—such as creating test suites for diverse optimization problems—requires coordination and foresight to ensure real-world relevance and usability.