Tootfinder

Data-Driven Fault Isolation in Linear Time-Invariant Systems: A Subspace Classification Approach
Mohammad Amin Sheikhi, Gabriel de Albuquerque Gleizer, Peyman Mohajerin Esfahani, Tam\'as Keviczky
https://arxiv.org/abs/2509.01347

Data-Driven Fault Isolation in Linear Time-Invariant Systems: A Subspace Classification Approach
We study the problem of fault isolation in linear systems with actuator and sensor faults within a data-driven framework. We propose a nullspace-based filter that uses solely fault-free input-output data collected under process and measurement noises. By reparameterizing the problem within a behavioral framework, we achieve a direct fault isolation filter design that is independent of any explicit system model. The underlying classification problem is approached from a geometric perspective, en…