Re-entry and Gliding Guidance Trajectory Optimization of Suborbital Spaceplane Using Dynamically Distributed Genetic Algorithm

Regarding the flight trajectory of a suborbital spaceplane, considering the situations such as abort flight, it is difficult to set the reference trajectory in advance. Therefore, a guidance algorithm is required for the suborbital spaceplane to generate the optimal trajectory flexibly during a return flight. Evolutionary algorithms that can search for solutions globally are effective methods for this purpose. Based on this idea, a return trajectory generation method using a dynamic distributed genetic algorithm (DynDGA) has been proposed. In this study, three improvements to the previously proposed DynDGA-based method are presented. First, the continuity of the angle-of-attack and bank-angle commands before and after the optimal trajectory update was ensured. Second, the angle-of-attack command satisfied the trim condition. Third, fitness was calculated based on hierarchical fuzzy logic. The effectiveness of the improved method was confirmed by trajectory generation simulation of a return flight of a suborbital spaceplane.