Delay propagation is a significant driver of flight delay in aviation networks, yet modelling it at a network-wide scale remains challenging. This study investigates to what extent scheduled max-plus linear systems, as used in railway delay modelling, can be applied to aviation networks. Using the Hawaiian Airlines network as a case study, a methodology is developed to model aircraft rotation and passenger transfer precedence relations within a max-plus linear system. The approach enables the calculation of stability indicators such as maximum cycle mean, recovery times, and network slack, as well as the simulation of delay propagation under various initial delay scenarios.

Results show that the recovery matrix is a valuable tool for identifying structurally vulnerable parts of the network and for assessing the impact of holding aircraft for transferring passengers. However, predictive accuracy of delay propagation for individual flights is limited, primarily due to uncertainties in process time estimation and incomplete knowledge of precedence relations. The 24-hour periodicity of aviation timetables, combined with large overnight buffers, further limits multi-day delay propagation modelling. These limitations are partly specific to the case under study and partly inherent to the deterministic, periodic structure of scheduled max-plus systems.

The study concludes that max-plus linear systems can provide meaningful insights into structural robustness and the systemic impact of schedule design choices, but their use for precise short-term delay prediction in aviation is constrained without high-quality operational data. Future work should explore integration of stochastic max-plus models, application to networks with shorter periodicity, and validation using airline-provided operational datasets.

The Flying-V is a tailless, V-shaped flying-wing type aircraft that promises to offer significant increases in aerodynamic efficiency. Due to its configuration, the Flying-V faces some control and stability related issues. These include limited control authority, pitch break tendencies and non-ideal handling qualities. To enhance the handling qualities of the Flying-V, Incremental Nonlinear Dynamic Inversion (INDI)-based flight control systems have been proposed. INDI, a sensor-based alternative to conventional Nonlinear Dynamic Inversion (NDI), is rooted in the principle of feedback linearization. Unlike NDI, INDI does not depend heavily on accurate on-board models (OBM), thereby offering increased robustness to aerodynamic uncertainties. However, singular perturbations—such as time delays, aeroelastic effects, and additional unmodeled or unknown dynamics—have been identified as challenges for INDI-based control laws. Various strategies have been explored to improve the overall robustness of INDI-based flight control systems, including outer-loop tuning and inversion loop augmentation strategies. In this research a multi-loop µ-optimal approach for designing robust inversion-based flight control laws is explored for the design of an explicit model-following pitch-rate control system for a short-period approximation of the Flying-V’s longitudinal dynamics. The design problem takes into account both regular and singular perturbations. To assess the robust stability and performance of the proposed control systems, a structured singular value analysis was performed. It was concluded that a multi-loop synthesis approach is capable of achieving better robust stability and performance levels when compared to either strictly inner-loop or outer-loop synthesis. As such, it can be concluded that multi-loop synthesis approaches are best capable of leveraging the robustness functionalities of multi-loop inversion-based control systems.