ABSTRACT

Dynamic optimization is a rather formal mathematical method using a drying model and an objective function. This chapter provides examples of dynamic optimization and reviews the dynamic optimization for drying operations and control. The general objective of a drying system is to reduce the water content of a product to a prescribed value. Energy represents the most significant operational cost in drying and the drying energy consumption should be reduced as far as possible. Operational strategies and protocols for batch-wise drying can be derived by smart usage of empirical knowledge or by application of dynamic optimization. Operational strategies and protocols for batch-wise drying can be derived by smart usage of empirical knowledge or by application of dynamic optimization. Dynamic optimization can also be applied as an element of model predictive control for freeze drying. The task of the controller in this application is to track the prescribed operational temperature trajectories and to keep quality as prescribed in an operational protocol.