A Data-Driven Approach To Preserve Safety and Reference Tracking for Constrained Cyber-Physical Systems Under Network Attacks
<|reference_start|>A Data-Driven Approach To Preserve Safety and Reference Tracking for Constrained Cyber-Physical Systems Under Network Attacks: This paper proposes a worst-case data-driven control architecture capable of ensuring the safety of constrained Cyber-Physical Systems under cyber-attacks while minimizing, whenever possible, potential degradation in tracking performance. To this end, a data-driven robust anomaly detector is designed to detect cyber-attack occurrences. Moreover, an add-on tracking supervisor module allows safe open-loop tracking control operations in case of unreliable measurements. On the plant side, a safety verification module and a local emergency controller are designed to manage severe attack scenarios that cannot be handled on the controller's side. These two modules resort to worst-case reachability and controllability data-driven arguments to detect potential unsafe scenarios and replace, whenever strictly needed, the tracking controller with emergency actions whose objective is to steer the plant's state trajectory in a predefined set of admissible and safe robust control invariant region until an attack-free scenario is restored. The effectiveness of the proposed solution has been shown through a simulation example.<|reference_end|>
@article{attar2024a,
    title={A Data-Driven Approach To Preserve Safety and Reference Tracking for
  Constrained Cyber-Physical Systems Under Network Attacks},
    author={Mehran Attar and Walter Lucia},
    journal={arXiv preprint arXiv:2410.00208},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.00208},
    primaryClass={eess.SY cs.SY math.OC}
}