Abstract

The growing deployment of unmanned aerial vehicles (UAVs) in safety-critical missions requires design methods that can assess reliability and fault tolerance early in development. Traditional safety analysis techniques are often cumbersome and restrict the exploration and optimization of complex multirotor architectures. While Model-Based Safety Assessment (MBSA) techniques overcome many of these limitations through automation and formal modeling, they still rely on binary failure assumptions and overlook the effects of failures on controllability and cross-domain propagation, which are key factors in systems where control authority depends directly on component health.
To address these limitations, this thesis extends MBSA by integrating controllability analysis and systematic failure-propagation modeling. The proposed framework first couples the Available Control Authority Index (ACAI)–based controllability assessment with MBSA using the AltaRica 3.0 language, linking the UAV’s physical architecture and control effectiveness to probabilistic reliability modeling.
A structured workflow defines the UAV configuration and reliability hypotheses, models the system architecture, evaluates controllability under all failure combinations, and embeds the results into the AltaRica model to generate quantitative reliability indicators and sensitivity measures. To move beyond binary assumptions, the Systematic Failure-Mode Propagation (SFMP) method is introduced, extending MBSA with multi-state component behavior, inter-domain propagation logic, and zonal integration. This extension enables not only the analysis of degradation and cascading effects but also the inclusion of criticality and zonal interactions, paving the way for future embedded common cause assessment capabilities, such as zonal and particular risk analysis.
A hexarotor UAV case study demonstrates the framework’s effectiveness, showing that integrating controllability and propagation modeling within MBSA enhances the realism and design value of UAV safety assessments, supporting the development of more reliable and fault-tolerant aerial systems.