2020
DOI: 10.48550/arxiv.2011.13730
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Abstract: In this article we propose a tractable nonlinear fault isolation filter along with explicit performance bounds for a class of linear dynamical systems in the presence of additive and multiplicative faults. The proposed filter architecture combines tools from model-based approaches in the control literature and regression techniques from machine learning. To this end, we view the regression operator through a system-theoretic perspective to develop operator bounds that are then utilized to derive performance bo… Show more

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Cited by 4 publications
(9 citation statements)
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References 23 publications
(60 reference statements)
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“…2 depicts the simulation results of a 500 sample long scenario. With this simulation, the effectiveness of the LPV diagnosis filter (with two different variations of the Lagrange multiplier γ) is shown and compared to an LTI diagnosis filter (as used in [14], generated for a velocity v x = 19.5 m/s). Here, the fault to be estimated is simulated as a realistic steering wheel offset in the context of automated driving:…”
Section: Case Study: Automated Drivingmentioning
confidence: 99%
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“…2 depicts the simulation results of a 500 sample long scenario. With this simulation, the effectiveness of the LPV diagnosis filter (with two different variations of the Lagrange multiplier γ) is shown and compared to an LTI diagnosis filter (as used in [14], generated for a velocity v x = 19.5 m/s). Here, the fault to be estimated is simulated as a realistic steering wheel offset in the context of automated driving:…”
Section: Case Study: Automated Drivingmentioning
confidence: 99%
“…In [14] an LTI fault detector is used in combination with non-linear regression for the detection and isolation of faults where multiple faults acting on the system dynamics have an identical input-output dynamical relationship. This work provides an extension to [14], where the LTI detector is extended for LPV systems.…”
Section: Introductionmentioning
confidence: 99%
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“…Their scheme guarantees bounded fault estimation errors. In [15], simultaneous additive and multiplicative process faults are considered. They address the fault estimation problem by decoupling process nonlinearities and perturbations from the estimation filter dynamics, and using regression techniques to approximately reconstruct fault signals.…”
Section: Introductionmentioning
confidence: 99%