Publication Date:
2019-07-13
Description:
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
Keywords:
Spacecraft Design, Testing and Performance
Type:
GSFC-E-DAA-TN19886
,
AAS/AIAA Spaceflight Mechanics Meeting; Jan 11, 2015 - Jan 15, 2015; Williamsburg, VA; United States
Format:
application/pdf
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