Open AccessOn-orbit Engine Thrust Prediction Algorithm for Geosynchronous Satellites based on Neural Network
Author(s) -
Wenjuan Yin,
Tao Song,
Zhen Lin
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/887/1/012040
Subject(s) - geosynchronous orbit , artificial neural network , thrust , orbit (dynamics) , computer science , satellite , genetic algorithm , algorithm , orbit determination , aerospace engineering , artificial intelligence , engineering , machine learning
Focused on the problem of complex in-orbit engine thrust prediction algorithm the geosynchronous satellite, a thrust prediction method based on the composition of the propulsion system is proposed in the paper. The method integrates theoretical model and neural network model, and the prediction model is simple and practical. In order to further improve the accuracy of the model, the in-orbit data was used to optimize the modified parameters using the multi-objective genetic algorithm NSGA-II. Finally, the optimized model is applied to different cases. The comparison between the simulation results and flight data shows that the accuracy of the optimized model is significantly improved, and the in-orbit thrust prediction method is correct and effective.