16 citations · 22 across the 7 of their papers we have counts for
3 papers · 1 filter
Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators
Jonas Nicodemus, Jonas Kneifl, Jörg Fehr +1
We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-informed neural networks (PINNs) are a promising…
Decomposition of flow data via gradient-based transport optimization
Felix Black, Philipp Schulze, Benjamin Unger
We study an optimization problem related to the approximation of given data by a linear combination of transformed modes. In the simplest case, the optimization problem reduces to…
From Time-Domain Data to Low-Dimensional Structured Models
Elliot Fosong, Philipp Schulze, Benjamin Unger
We present a framework for constructing a structured realization of a linear time-invariant dynamical system solely from a discrete sampling of an input and output trajectory of th…