Generalized Mean Robustness for Signal Temporal Logic

Robustness functions provide quantitative scores to measure the satisfaction of temporal logic formulas. We introduce a general class of parameterized robustness functions for signal temporal logic (STL), and demonstrate how it can be used for control problems involving STL specifications. We employ power means and generalized functional means to capture robust satisfaction over space and time. We show that our general definition encompasses many of the STL robustness functions in the literature. Most importantly, we show how that our notion of robustness addresses the two main limitations of the the traditional robustness (masking and locality), which currently limit using robustness-based approaches for control. The proposed robustness function parameters affect the conservativeness of the score, and can be chosen based on desired performance. We show how the proposed robustness can be used for control.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2024-10-16
DOI
https://doi.org/10.1109/tac.2024.3482104
Citations
3
Primary Topic
Formal Methods in Verification
Type
article
Field-Weighted Citation Impact
1.08

Funders

Controls
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article

Generalized Mean Robustness for Signal Temporal Logic

Noushin Mehdipour, Cristian-Ioan Vasile, Călin Belta
3 citations
IEEE Transactions on Automatic Control
Formal Methods in Verification
1.08
article

Generalized Mean Robustness for Signal Temporal Logic

Noushin Mehdipour, Cristian-Ioan Vasile, Călin Belta
article en
3 citations

Abstract

Robustness functions provide quantitative scores to measure the satisfaction of temporal logic formulas. We introduce a general class of parameterized robustness functions for signal temporal logic (STL), and demonstrate how it can be used for control problems involving STL specifications. We employ power means and generalized functional means to capture robust satisfaction over space and time. We show that our general definition encompasses many of the STL robustness functions in the literature. Most importantly, we show how that our notion of robustness addresses the two main limitations of the the traditional robustness (masking and locality), which currently limit using robustness-based approaches for control. The proposed robustness function parameters affect the conservativeness of the score, and can be chosen based on desired performance. We show how the proposed robustness can be used for control.

IEEE Transactions on Automatic ControlVol. 70(3)
Lehigh University (US), University of Maryland, College Park (US)
Air Force Office of Scientific Research
Openalex Percentile: Top 20%
Formal Methods in Verification
1.08
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Generalized Mean Robustness for Signal Temporal Logic — Noushin Mehdipour, Cristian-Ioan Vasile, et al. · IEEE Transactions on Automatic Control (2024) | TGRS Research Map | TGRS