Intelligent Flight-Trajectory Generation to Maximize Safe-Outcome Probability After a Distress Event

摘要

A flight trajectory generation method called the distressed-aircraft-recovery technique for maximum safe-noutcome probability (DART_MSOP), based on integration of three new algorithms, is developed that maximizesnsafe-outcome probability after a distress event by incorporating an abort airport together with a model of currentnaircraft dynamics. Several abort-probabilitymodels are studied under various constraints. The first new algorithm,na statistical-based initial-turn-determination algorithm, is developed to advise pilots to a reachable best landing sitenimmediately after the distress event and before using the second new algorithm, a high-fidelity flight trajectoryngeneration algorithm. A third new algorithm determines the flight maneuver for guidance of a perpetual-turning-nattitude aircraft to fly the trajectory generated by the second algorithm. The third algorithm is only used if thenaircraft has stuck controls or a similar malfunction that generates a nonzero amount of bank angle and causes thenaircraft to turn only in one direction. As a three-dimensional high-fidelity algorithm, the second algorithmconsidersnthe probability of an abort to increase overall survivability byminimizing expected flight-path length as it shapes thentrajectory. The performance of this new intelligent flight trajectory determination method DART_MSOP isnevaluated using a case study based on a hypothetical in-flight distressed transport aircraft in northern California.nNumerical simulations include variable failure rates to simulate different in-flight distress conditions, and multiplenfixes along the path to accommodate realistic trajectories. DART_MSOP intelligent flight trajectory determinationnmethod should increase aviation safety if these algorithms are implemented in aircraft avionics systems.