Trajectory generation and display for free flight
This work addresses trajectory generation for free flight in aviation, presenting an incremental improvement by applying neural approximators to an existing optimal control problem.
The study tackled the problem of generating minimum-time aircraft trajectories for relative guidance to join a leader's track, using neural networks to approximate optimal trajectories adaptively during operation, with simulation results demonstrated on two wide-body aircraft.
In this study a new approach is proposed for the generation of aircraft trajectories. The relative guidance of an aircraft, which is aimed to join in minimum time the track of a leader aircraft, is particularly considered. In a first place, a minimum time relative convergence problem is considered and optimal trajectories are characterized. Then the synthesis of a neural approximator for optimal trajectories is discussed. Trained neural networks are used in an adaptive manner to generate intent trajectories during operation. Finally simulation results involving two wide body aircraft are presented.