An integrated operational safety assurance method for reconfigurable flight control systems based on uncertainty quantification and resilience decision-making
The dynamic reconfigurability of civil aircraft flight control systems (FCS) enhances mission adaptability yet introduces significant operational uncertainty. Traditional static safety assurance methods often fail to cope with such real-time variations. To address this, this paper proposes an integrated safety assurance framework that synergistically combines uncertainty quantification, resilience engineering, and multi-criteria decision-making. First, this paper establishes a multidimensional uncertainty ontology encompassing environmental, system-internal, human–machine, and reconfiguration factors, which is quantified using hybrid probabilistic graphical models. Building on this foundation, this paper develops a closed-loop resilience architecture that embeds the four core capabilities of resilience engineering (anticipating, monitoring, responding, learning) to enable dynamic risk perception and adaptive reconfiguration. Specifically, this paper utilizes a time-evolving multi-attribute utility function coupled with online optimization to support worst-case-oriented robust decision-making. Central to the approach is a time-evolving multi-attribute utility function coupled with online optimization, which supports worst-case-oriented robust decision-making. Validation through a dual-disturbance scenario (severe weather and sensor degradation) demonstrates significant improvements in decision quality and operational resilience. Compared with a traditional fault tree analysis (FTA) baseline under identical simulation settings, the proposed framework demonstrates up to a 25%–35% improvement in the timeliness of risk state identification and an approximately 30–40% enhancement in decision robustness under sensor degradation and dynamic environmental uncertainty.