Global Trajectory Optimization Framework via Multi-Fidelity Approach Supported by Machine Learning and Primer Vector Theory for Advanced Space Mission Design

Satoshi Ueda, Hideaki Ogawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

With the advancement of space missions and increasing complexity of spacecraft systems, traditional development methods that rely on experience and past examples are approaching the limits. A flexible and robust design space search method based on a systematic approach is required to accomplish challenging space missions. This paper presents a global trajectory optimization framework via a multi-fidelity approach that utilizes a graphics processing unit (GPU) for low-fidelity initial solution search and a central processing unit (CPU) to determine high-fidelity feasible solutions compliant with imposed constraints. A mission scenario employing transfer from a near-rectilinear halo orbit (NRHO) to a low lunar orbit (LLO) is considered to demonstrate the proposed framework, which consists of the following specific processes: (1) identifying a multitude of feasible trajectories as potential global optimum solutions with the aid of super-parallelized trajectory propagation using single-precision GPU cores; and then (2) determining accurate trajectories by means of gradient-based optimization incorporating double-precision propagation using CPU cores. The resultant trajectories are assessed via machine learning to identify the clustering structure, and verified in the light of the primer vector theory that evaluates local optimality in terms of minimum fuel consumption.

本文言語英語
ホスト出版物のタイトルProceedings of 2020 SICE International Symposium on Control Systems, SICE ISCS 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ69-76
ページ数8
ISBN(電子版)9784907764647
DOI
出版ステータス出版済み - 3 2020
イベント2020 SICE International Symposium on Control Systems, SICE ISCS 2020 - Tokushima, 日本
継続期間: 3 3 20203 5 2020

出版物シリーズ

名前Proceedings of 2020 SICE International Symposium on Control Systems, SICE ISCS 2020

会議

会議2020 SICE International Symposium on Control Systems, SICE ISCS 2020
国/地域日本
CityTokushima
Period3/3/203/5/20

All Science Journal Classification (ASJC) codes

  • 自動車工学
  • 制御およびシステム工学
  • 計算数学
  • 制御と最適化
  • モデリングとシミュレーション
  • 人工知能
  • 航空宇宙工学

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