Open AccessLow-Thrust Many-Revolution Trajectory Optimization via Differential Dynamic Programming and a Sundman Transformation
Author(s) -
Jonathan D. Aziz,
Jeffrey S. Parker,
Daniel J. Scheeres,
Jacob A. Englander
Publication year - 2018
Publication title -
the journal of the astronautical sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.698
H-Index - 46
eISSN - 2195-0571
pISSN - 0021-9142
DOI - 10.1007/s40295-017-0122-8
Subject(s) - trajectory optimization , thrust , orbital maneuver , spacecraft , perturbation (astronomy) , trajectory , orbit (dynamics) , rendezvous , aerospace engineering , geocentric model , computer science , optimization problem , control theory (sociology) , physics , mathematics , mathematical optimization , geodesy , geology , engineering , control (management) , astronomy , artificial intelligence , quantum mechanics
Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging optimization problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory optimization about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to an orbit angle and performing the optimization with differential dynamic programming. Fuel-optimal geocentric transfers are computed with the transfer duration extended up to 2000 revolutions. The flexibility of the approach to higher fidelity dynamics is shown with Earth’s J2 perturbation and lunar gravity included for a 500 revolution transfer.
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