Data-based control of heterogeneous population systems

Distributed population systems are characterized by a large number of similar components that differ in some variables. This type of systems occurs in several processes in (bio-)chemical engineering, and tools for simulation, monitoring and control of these heterogeneous system dynamics are required to strive for optimal process operation. Methods towards modelling and control of heterogeneous distributed population systems will be developed. Models will be constructed that rely on high-throughput process measurements in combination with so-called Gaussian processes, a statistical modelling technique which is able to include uncertainty in the heterogeneity. Such methodological framework allows the prediction of process dynamics and the application of model-predictive process control to heterogeneous distributed population systems with in the context of (bio-)chemical engineering.