1st ACT global trajectory optimisation competition: Results found at DLR

This paper describes the DLR team solution method and results for ESA's 1st ACT global trajectory optimisation competition problem. The other articles in this volume demonstrate that the design and the optimisation of low-thrust trajectories are usually a very difficult task that involves much experience and expert knowledge. We have used evolutionary neurocontrol-a method that fuses artificial neural networks and evolutionary algorithms-to find a solution for the given low-thrust trajectory optimisation problem. This method requires less experience/knowledge in astrodynamics and in optimal control theory than the traditional methods. In this paper, the implementation of evolutionary neurocontrol is outlined and its performance for the given problem is shown.