@inproceedings{cf9d161acc984421830582ff56620f33,
title = "Multi-constraint Online Guidance Method Based on Meta-learning",
abstract = "In this study, an online guidance method based on the few-shot learning theory is proposed. First of all, a muti-constrained optimal control model is constructed for the guidance problem. Secondly, through using the meta-learning theory in the field of few-shot learning, a highly reliable and non-iterative online guidance method considering multiple constraints that can quickly adapt to a variety of guidance problems of the same category is developed. The effectiveness of the proposed method is verified by numerical simulations.",
keywords = "Deep learning, Few-shot learning, Meta-learning, Multi-constraint, Online guidance",
author = "Chao Li and Fenfen Xiong and Yue Zhao",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2022 ; Conference date: 05-08-2022 Through 07-08-2022",
year = "2023",
doi = "10.1007/978-981-19-6613-2_226",
language = "English",
isbn = "9789811966125",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "2320--2331",
editor = "Liang Yan and Haibin Duan and Yimin Deng and Liang Yan",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control",
address = "Germany",
}