SUPR
PINNs for control
Dnr:

NAISS 2024/22-758

Type:

NAISS Small Compute

Principal Investigator:

Matthieu Barreau

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2024-05-31

End Date:

2024-12-01

Primary Classification:

20202: Control Engineering

Webpage:

Allocation

Abstract

The goal of this research project is the development of physics-informed learning techniques to analyze the stability of dynamical systems. In particular, we are interested in characterizing if, and under what conditions, a system evolves toward an equilibrium point. The objective then is to establish a theoretical framework based on Lyapunov theory for learning-based stability analysis and to develop a modular and extensible implementation of this framework.