Identification and Control for Batch Crystallization
In many cases, stringent requirements on the quality of the final product have to be met. The control of a number of variables throughout the batch infuences the quality of the final product to a large extent. For this reason, the industries in the field are interested into the introduction of advanced automation technology.
Batch operations bring both challanges and opportunities for identification and control. On the one hand, batch process system are operated over a wide dynamical range. For this reason, strategies based on linearization around a single operating point lead often to poor results. In some cases, first-principles models describing the full nonlinear dynamic behavior are available. Unfortunately, these models are often either not sufficiently accurate for control purposes.
On the other hand, the repetitive nature of batch processing enables iterative techniques based on the information collected during the previous runs.
During my Ph.D. I developed, analyzed, and experimentally validated iterative identification and control strategies suitable for industrial batch processes such as batch cooling crystallization. The focus of my reaserch was in particular on
- Iterative Identification and Control
- Batch-to batch Identification, Optimization & Control
- Experiment Design.