Lunar Ascent Nominal Trajectory Optimization based on UKF Parameter Estimation

DOI

10.2991/iiicec-15.2015.176How to use a DOI?

Keywords

lunar ascent; nominal trajectory; two-point boundary value problem; unscented Kalman filter; parameter estimation

Abstract

Focused on the optimization of lunar ascent nominal trajectory, an algorithm based on the unscented Kalman filter (UKF) parameter estimation is proposed in this paper. The optimization of lunar ascent nominal trajectory problem requiring minimum fuel is formulated as a two-point boundary value problem (TPBVP) through the maximum principle. By treating the initial values of the costate variables as parameters to be estimated and setting the deviation of terminal values as target observations, the TPBVP is then transformed into a parameter estimation problem and solved by the UKF parameter estimation algorithm. Numerical simulation results demonstrate that the algorithm can be used to optimize lunar ascent nominal trajectory, it can also overcome the difficulty of guessing the initial values of the costate variables, and the calculating efficiency is higher than traditional optimization algorithm under the premise of guaranteed accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiang Chen
AU  - Fengbo Wang
AU  - Changhong Dong
PY  - 2015/03
DA  - 2015/03
TI  - Lunar Ascent Nominal Trajectory Optimization based on UKF Parameter Estimation
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 780
EP  - 787
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.176
DO  - 10.2991/iiicec-15.2015.176
ID  - Chen2015/03
ER  -