Dynamic Networks: Data-Driven Modeling and Control

Demands on engineering systems require the ability to monitor and optimize the behavior of dynamic systems that are interconnected as networks of systems. We develop methods and tools for the modeling of dynamic networks on the basis of operational data, to be used as a basis for model-based operations as surveillance, detection, monitoring and control. For this purpose we build on contributions from the fields of system identification, machine learning, data science and dynamic systems & control. Potential domains of applications include distributed (smart) power systems, industrial production processes, transportation networks and high-tech mechatronic systems.