Quantifying the Safety of Trajectories using Peak-Minimizing Control

Fuente: arXiv
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Hauptverfasser: Miller, Jared, Sznaier, Mario
Format: Preprint
Veröffentlicht: 2023
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author Miller, Jared
Sznaier, Mario
author_facet Miller, Jared
Sznaier, Mario
contents This work quantifies the safety of trajectories of a dynamical system by the perturbation intensity required to render a system unsafe (crash into the unsafe set). Computation of this measure of safety is posed as a peak-minimizing optimal control problem. Convergent lower bounds on the minimal peak value of controller effort are computed using polynomial optimization and the moment-Sum-of-Squares hierarchy. The crash-safety framework is extended towards data-driven safety analysis by measuring safety as the maximum amount of data corruption required to crash into the unsafe set.
format Preprint
id arxiv_https___arxiv_org_abs_2303_11896
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Quantifying the Safety of Trajectories using Peak-Minimizing Control
Miller, Jared
Sznaier, Mario
Optimization and Control
Systems and Control
49N90, 90C23, 93C10, 90C17, 93-08
This work quantifies the safety of trajectories of a dynamical system by the perturbation intensity required to render a system unsafe (crash into the unsafe set). Computation of this measure of safety is posed as a peak-minimizing optimal control problem. Convergent lower bounds on the minimal peak value of controller effort are computed using polynomial optimization and the moment-Sum-of-Squares hierarchy. The crash-safety framework is extended towards data-driven safety analysis by measuring safety as the maximum amount of data corruption required to crash into the unsafe set.
title Quantifying the Safety of Trajectories using Peak-Minimizing Control
topic Optimization and Control
Systems and Control
49N90, 90C23, 93C10, 90C17, 93-08
url https://arxiv.org/abs/2303.11896