Time-Robust Control for STL Specifications
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Abstract (arXiv)
We present a robust control framework for time-critical systems in which satisfying real-time constraints robustly is of utmost importance for the safety of the system. Signal Temporal Logic (STL) provides a formal means to express a large variety of real-time constraints over signals and is suited for planning and control purposes as it allows us to reason about the time robustness of such constraints. The time robustness of STL particularly quantifies the extent to which timing uncertainties can be tolerated without violating real-time specifications. In this paper, we first pose a control problem in which we aim to find an optimal input sequence to a control system that maximizes the time robustness of an STL constraint. We then propose a Mixed Integer Linear Program (MILP) encoding and provide correctness guarantees along with a complexity analysis of the encoding. We also show in two case studies that maximizing STL time robustness allows to account for timing uncertainties of the underlying control system.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Apr 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2022Conformal Quantitative Predictive Monitoring of STL Requirements for Stochastic Processescited by 12
- 2023Learning-Based Approaches to Predictive Monitoring with Conformal Statistical Guaranteescited by 2
- 2025Conformal Predictive Monitoring for Multi-Modal Scenarioscited by 1
- 2026Spatiotemporal Robustness of Temporal Logic Tasks using Multi-Objective Reasoningcited by 1
- 2026Spatiotemporal Robustness of Temporal Logic Tasks using Multi-Objective Reasoning28 Jan 2026
- 2025Conformal Predictive Monitoring for Multi-Modal Scenarios1 Sep 2025
- 2023Learning-Based Approaches to Predictive Monitoring with Conformal Statistical Guarantees4 Dec 2023
- 2022Conformal Quantitative Predictive Monitoring of STL Requirements for Stochastic Processes4 Nov 2022