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Main Authors: Galarza-Jimenez, Felipe, Zamani, Majid, Jafarpour, Saber
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.16660
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author Galarza-Jimenez, Felipe
Zamani, Majid
Jafarpour, Saber
author_facet Galarza-Jimenez, Felipe
Zamani, Majid
Jafarpour, Saber
contents This paper presents a novel data-driven framework for the robust safety verification and safe control synthesis of unknown monotone discrete-time systems. While existing data-driven safety analysis approaches are often either heuristic in nature or require large amounts of data to provide rigorous guarantees, we leverage the structural property of monotonicity to significantly reduce data requirements while still ensuring formal safety guarantees. Our approach is built upon a new class of certificates called dominance functions, constructed directly from collected system trajectories, which themselves need not be safe. By exploiting the monotone structure of the dynamics, we show that dominance functions are (i) dissipative, meaning that they decrease monotonically along system trajectories, and (ii) sufficiently \expressive to characterize safety certificates for monotone systems. Together, these properties establish dominance functions as principled building blocks for the systematic construction of formal safety certificates directly from trajectory data. For both robust safety verification and safe control synthesis, we develop an efficient sampling-based optimization framework that searches for safety certificates represented as linear combinations of dominance functions constructed from collected trajectories. We validate our data-driven framework on two monotone systems by successfully deriving safety certificates from a small number of trajectories.
format Preprint
id arxiv_https___arxiv_org_abs_2605_16660
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Trajectory-based Safety of Monotone Systems: Verification and Control Synthesis
Galarza-Jimenez, Felipe
Zamani, Majid
Jafarpour, Saber
Systems and Control
This paper presents a novel data-driven framework for the robust safety verification and safe control synthesis of unknown monotone discrete-time systems. While existing data-driven safety analysis approaches are often either heuristic in nature or require large amounts of data to provide rigorous guarantees, we leverage the structural property of monotonicity to significantly reduce data requirements while still ensuring formal safety guarantees. Our approach is built upon a new class of certificates called dominance functions, constructed directly from collected system trajectories, which themselves need not be safe. By exploiting the monotone structure of the dynamics, we show that dominance functions are (i) dissipative, meaning that they decrease monotonically along system trajectories, and (ii) sufficiently \expressive to characterize safety certificates for monotone systems. Together, these properties establish dominance functions as principled building blocks for the systematic construction of formal safety certificates directly from trajectory data. For both robust safety verification and safe control synthesis, we develop an efficient sampling-based optimization framework that searches for safety certificates represented as linear combinations of dominance functions constructed from collected trajectories. We validate our data-driven framework on two monotone systems by successfully deriving safety certificates from a small number of trajectories.
title Trajectory-based Safety of Monotone Systems: Verification and Control Synthesis
topic Systems and Control
url https://arxiv.org/abs/2605.16660