Control on Networks: Modeling, Learning and applications

Networks of nonlinear hyperbolic systems arise in many real world applications, e.g. planar networks of vibrating strings, shearable beams, gas networks and shallow water systems. Often such networks involve dynamical boundary conditions, for example when a network of strings contains one or several point-masses. This talk is an introduction of controllability properties and methods for networked 1D hyperbolic systems based on results obtained by the speaker and her collaborators in recent years. Modelling, analysis of the underlying dynamics and exact controllability of several physical models will be presented at first. Some recent numerical experiments with Physics-Informed Neural Networks (PINNs) show interesting possibilities for future research on the interface between control and machine learning.

Yue Wang was educated  from Bachelor to PhD at Fudan University, Shanghai, China. Her PhD was conducted in the research group Analysis and Applied PDEs located at Shanghai Center of Mathematics, and was supervised by Prof. Tatsien Li. In 2019, she received the Doctor degree in mathematics and applied mathematics from Fudan University.  After that, she did a 2-year PostDoc at the Chair of Applied Mathematics II led by Günter Leugering in FAU Erlangen-Nuremberg (Friedrich-Alexander-Universität Erlangen-Nürnberg)，and then 1 year working with Enrique Zuazua at the Chair of Dynamics, Control, Machine Learning and Numerics.