Real-time adaptive prediction of loss-of-control margins on a fourth order aircraft

Abstract

Loss-of-Control events continue to be the most significant contributing factor to air accidents worldwide. Predictive systems capable of warning pilots of impending entry into control loss have the potential to further improve safety in flight. Towards this goal, an early warning mechanism is developed to predict an aircraft’s safe control envelope and warn pilots of future impending excursion of the safe flight envelope, and thus entry into loss-of-control. The adaptive architecture predicts the aircraft's proximity to its control loss boundaries, and determines critical control deflection, rate, and acceleration limits that would drive the aircraft to control loss n seconds in the future. The architecture utilizes 2nd order analytical analysis techniques applied to the 4th order aircraft through a modal decomposition process, allowing for mathematically and computationally efficient online prediction of impending control loss. Adaptive parameter estimation is implemented to facilitate real-time modeling error identification, in order to account for uncertainties such as failures or modeling error in the aircraft. A pilot advisory display presents the predicted control boundaries to the pilot through head-up augmented-reality technologies, providing pre-emptive warning of impending entry into control loss within the look-ahead prediction window. The architectures are applied to a 4th order light business jet model in simulation, and results demonstrate, across various initial conditions, successful prediction of the critical control limits that should not be exceeded in order to avoid entry into control loss.