Journal of Astronautics ›› 2021, Vol. 42 ›› Issue (1): 61-73.doi: 10.3873/j.issn.1000-1328.2021.01.007

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The Application of Aerodynamic Coefficients Prediction Technique via Artificial Intelligence Method to Rocket First Stage Landing Area Control Project

DU Tao, XU Chen zhou, WANG Guo hui, GONG Yu kun, HE Wei,MOU Yu, LI Zhou yang, SHEN Dan, CHENG Xing, GAO Jia yi, HAN Zhong hua   

  1. 1. Beijing Institute of Astronautical Systems Engineering, Beijing 100076, China; 2. National Key Laboratory of Science and  Technology on Aerodynamic Design and Research, School of Aeronautics, Northwestern Polytechnical University, Xian 710072, China
  • Received:2020-05-13 Revised:2020-09-25 Online:2021-01-15 Published:2021-01-25

Abstract: A novel approach of predicting aerodynamic data via artificial intelligence technique is proposed in this article. Based on wind tunnel tests of partial test states, combined with several CFD results, machine learning via Kriging model is used to predict the whole aerodynamic characteristics to shorten the development cycle and reduce the expensive wind tunnel tests as many as possible. After solving several key technical problems such as the selection of correlation functions, hyper parameters training, data verification and application of man in loop technique, the complete set of aerodynamic data was obtained successfully and used to the control law design in the rocket first stage landing area control project with grid fins. The correctness of the proposed method was validated by a flight test on 26th July, 2019, which was carried out successfully for the first time in China. At the end, the grading of technology maturity degree for the artificial intelligence technique is presented to evaluate application to aerodynamic engineering design problems.

Key words: Artificial intelligence, Machine learning, Aerodynamic characteristics, Grid fin, Rocket first stage landing area control, Technology classification

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