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eess.SY2026

Detectability of Subtle Anomalies in Dynamical Systems via Log-Likelihood Ratio

Alejandro Penacho Riveiros, Matthieu Barreau, Nicola Bastianello

Industrial control applications require detecting system anomalies as accurately and quickly as possible to enable prompt maintenance. In this context, it is common to consider sev…

eess.SY2026

Model-free Anomaly Detection for Dynamical Systems with Gaussian Processes

Alejandro Penacho Riveiros, Nicola Bastianello, Matthieu Barreau

In this paper we address the problem of detecting differences or anomalies in a dynamical system, based on historical data of nominal operations. This problem encompasses quality c…

eess.SY2026

Physics-Informed Detection of Friction Anomalies in Satellite Reaction Wheels

Alejandro Penacho Riveiros, Nicola Bastianello, Karl H. Johansson +1

As the number of satellites in orbit has increased exponentially in recent years, ensuring their correct functionality has started to require automated methods to decrease human wo…

eess.SY2026

Second Order Physics-Informed Learning of Road Density using Probe Vehicles

S. Betancur Giraldo, J. MÃ¥rtensson, M. Barreau

We propose a Physics Informed Learning framework for reconstructing traffic density from sparse trajectory data. The approach combines a second-order Aw-Rascle and Zhang model with…

eess.SY2025

Modeling and Physics-Enhanced Fault Detection in Wastewater Pump Stations

Katayoun Eshkofti, Henrik Sandberg, Mikael Nilsson +1

Monitoring wastewater pump stations is essential because they are critical infrastructure. However, monitoring is still often performed manually due to the lack of suitable algorit…