Conformal Recovery-Deadline Certificates for Runtime Assurance of Adapting Controllers

Researchers introduce conformal recovery-deadline certificates, a new runtime assurance mechanism that allows adaptive controllers to safely recover from faults without premature shutdown. The method uses statistical bounds to distinguish between controllers capable of self-correction and those that will fail, applying a verified backstop only when necessary.

Runtime assurance systems protect safety-critical applications by switching to fail-safe controls when risks emerge. Traditional approaches use latching rules that immediately trip on any safety violation, an effective strategy for controllers that diverge uncontrollably. However, modern adaptive controllers present a paradox: they intentionally enter unsafe transient states during fault recovery, requiring sensor data and system excitation to identify and correct problems. Standard latching shields incorrectly interpret this necessary recovery phase as system failure, disabling controllers that would have successfully self-corrected.

This research addresses a fundamental tension in autonomous system design. The conformal recovery-deadline certificate offers a distribution-free statistical method that bounds recovery time with guaranteed coverage, licensing controlled delays before fallback activation. The approach elegantly separates two concerns: autonomy (governed by statistical guarantees) and safety (governed by verified monitoring), enabling adaptive systems to operate more effectively while maintaining formal safety properties.

The work demonstrates practical relevance across unrelated domains, from spacecraft attitude control to robotic systems, suggesting the mechanism transcends domain-specific engineering. The proven coverage properties—including extensions for fault-distribution shifts and conditional guarantees—indicate mathematical rigor supporting real-world deployment. For developers of safety-critical autonomous systems, this framework could significantly reduce false-positive shield activations that currently suppress functional recovery behaviors. The research establishes a principled path toward more efficient autonomous control without compromising safety assurance, particularly valuable for applications where adaptive learning and fault tolerance are essential.

• →Conformal recovery-deadline certificates enable adaptive controllers to attempt self-correction before safety fallback triggers, matching modern autonomous system needs
• →The method separates autonomy (statistical coverage) from safety (verified monitoring), creating a more nuanced runtime assurance approach than binary latching rules
• →Domain-general validation on spacecraft and inverted pendulum systems demonstrates applicability across diverse safety-critical applications
• →Distribution-free finite-sample bounds guarantee coverage without requiring assumptions about fault distributions, supporting real-world deployment
• →The mechanism reduces suppression of capable controllers during legitimate recovery transients, improving system efficiency while maintaining formal safety properties