115 citations · 435 across the 67 of their papers we have counts for
3 papers · 1 filter
Safe Physics-Informed Machine Learning for Dynamics and Control
Jan Drgona, Truong X. Nghiem, Thomas Beckers +6
This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models…
Physics-informed machine learning for sensor fault detection with flight test data
Brian M. de Silva, Jared Callaham, Jonathan Jonker +7
We develop data-driven algorithms to fully automate sensor fault detection in systems governed by underlying physics. The proposed machine learning method uses a time series of typ…
Learning Precisely Timed Feedforward Control of the Sensor-Denied Inverted Pendulum
Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton
Time delays due to signal latency, computational complexity, and sensor-denied environments, pose a critical challenge in both engineered and biological control systems. In this wo…