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Main Authors: Daniels, Annalena, Teutsch, Johannes, Kleindienst, Fabian, Leibold, Marion, Wollherr, Dirk
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2508.12010
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author Daniels, Annalena
Teutsch, Johannes
Kleindienst, Fabian
Leibold, Marion
Wollherr, Dirk
author_facet Daniels, Annalena
Teutsch, Johannes
Kleindienst, Fabian
Leibold, Marion
Wollherr, Dirk
contents This paper proposes a novel framework for active fault diagnosis and parameter estimation in linear systems operating in closed-loop, subject to unknown but bounded faults. The approach integrates set-membership identification with a cost function designed to accelerate fault identification. Informative excitation is achieved by minimizing the size of the parameter uncertainty set, which is approximated using ellipsoidal outer bounds. Combining this formulation with a scheduling parameter enables a transition back to nominal control as confidence in the model estimates increases. Unlike many existing methods, the proposed approach does not rely on predefined fault models. Instead, it only requires known bounds on parameter deviations and additive disturbances. Robust constraint satisfaction is guaranteed through a tube-based model predictive control scheme. Simulation results demonstrate that the method achieves faster fault detection and identification compared to passive strategies and adaptive ones based on persistent excitation constraints.
format Preprint
id arxiv_https___arxiv_org_abs_2508_12010
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Active Fault Identification and Robust Control for Unknown Bounded Faults via Volume-Based Costs
Daniels, Annalena
Teutsch, Johannes
Kleindienst, Fabian
Leibold, Marion
Wollherr, Dirk
Optimization and Control
Systems and Control
This paper proposes a novel framework for active fault diagnosis and parameter estimation in linear systems operating in closed-loop, subject to unknown but bounded faults. The approach integrates set-membership identification with a cost function designed to accelerate fault identification. Informative excitation is achieved by minimizing the size of the parameter uncertainty set, which is approximated using ellipsoidal outer bounds. Combining this formulation with a scheduling parameter enables a transition back to nominal control as confidence in the model estimates increases. Unlike many existing methods, the proposed approach does not rely on predefined fault models. Instead, it only requires known bounds on parameter deviations and additive disturbances. Robust constraint satisfaction is guaranteed through a tube-based model predictive control scheme. Simulation results demonstrate that the method achieves faster fault detection and identification compared to passive strategies and adaptive ones based on persistent excitation constraints.
title Active Fault Identification and Robust Control for Unknown Bounded Faults via Volume-Based Costs
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2508.12010