Computing Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment via Trajectory Sensitivities

Fuente: arXiv
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Auteur principal: Fisher, Michael W.
Format: Preprint
Publié: 2025
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author Fisher, Michael W.
author_facet Fisher, Michael W.
contents Physical systems experience nonlinear disturbances which have the potential to disrupt desired behavior. For a particular disturbance, whether or not the system recovers from the disturbance to a desired stable equilibrium point depends on system parameter values, which are typically uncertain and time-varying. Therefore, to quantify proximity to vulnerability we define the safety margin to be the smallest change in parameter values from a nominal value such that the system will no longer be able to recover from the disturbance. Safety margins are valuable but challenging to compute as related methods, such as those for robust region of attraction estimation, are often either overly conservative or computationally intractable for high dimensional systems. Recently, we developed algorithms to compute safety margins efficiently and non-conservatively by exploiting the large sensitivity of the system trajectory near the region of attraction boundary to small perturbations. Although these algorithms have enjoyed empirical success, they lack theoretical guarantees that would ensure their generalizability. This work develops a novel characterization of safety margins in terms of trajectory sensitivities, and uses this to derive well-posedness and convergence guarantees for these algorithms, enabling their generalizability and successful application to a large class of nonlinear systems.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07498
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Computing Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment via Trajectory Sensitivities
Fisher, Michael W.
Systems and Control
93D09, 93D99, 37D10, 37D05
Physical systems experience nonlinear disturbances which have the potential to disrupt desired behavior. For a particular disturbance, whether or not the system recovers from the disturbance to a desired stable equilibrium point depends on system parameter values, which are typically uncertain and time-varying. Therefore, to quantify proximity to vulnerability we define the safety margin to be the smallest change in parameter values from a nominal value such that the system will no longer be able to recover from the disturbance. Safety margins are valuable but challenging to compute as related methods, such as those for robust region of attraction estimation, are often either overly conservative or computationally intractable for high dimensional systems. Recently, we developed algorithms to compute safety margins efficiently and non-conservatively by exploiting the large sensitivity of the system trajectory near the region of attraction boundary to small perturbations. Although these algorithms have enjoyed empirical success, they lack theoretical guarantees that would ensure their generalizability. This work develops a novel characterization of safety margins in terms of trajectory sensitivities, and uses this to derive well-posedness and convergence guarantees for these algorithms, enabling their generalizability and successful application to a large class of nonlinear systems.
title Computing Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment via Trajectory Sensitivities
topic Systems and Control
93D09, 93D99, 37D10, 37D05
url https://arxiv.org/abs/2501.07498