Robust adaptive neural fault-tolerant control of hypersonic flight vehicle

Yuyan Guo; Qiang Wang; Bin Xu

doi:10.1007/978-981-10-5230-9_5

Robust adaptive neural fault-tolerant control of hypersonic flight vehicle

Yuyan Guo
, Qiang Wang
, Bin Xu

自动化学院

Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

This paper proposes a fault-tolerant back-stepping control method for the hypersonic flight vehicle. An adaptive law is proposed to make sure that the normal actuators could compensate the ineffective actuators while failure exists. Meanwhile, the RBF NN is employed to estimate the unknown nonlinearity of the model. The simulation results verify the effectiveness of the proposed approach.

源语言	英语
主期刊名	Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers
编辑	Fuchun Sun, Huaping Liu, Dewen Hu
出版商	Springer Verlag
页	44-51
页数	8
ISBN（印刷版）	9789811052293
DOI	https://doi.org/10.1007/978-981-10-5230-9_5
出版状态	已出版 - 2017
活动	3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016 - Beijing, 中国期限: 19 11月 2016 → 23 11月 2016

丛书

姓名	Communications in Computer and Information Science
卷	710
ISSN（印刷版）	1865-0929

会议

会议	3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016
国家/地区	中国
市	Beijing
时期	19/11/16 → 23/11/16

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10.1007/978-981-10-5230-9_5

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引用此

Guo, Y., Wang, Q., & Xu, B. (2017). Robust adaptive neural fault-tolerant control of hypersonic flight vehicle. 在 F. Sun, H. Liu, & D. Hu (版本), Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers (页码 44-51). (Communications in Computer and Information Science; 卷 710). Springer Verlag. https://doi.org/10.1007/978-981-10-5230-9_5

@inproceedings{126cf30486db45f7b4d38a8747a502b6,

title = "Robust adaptive neural fault-tolerant control of hypersonic flight vehicle",

abstract = "This paper proposes a fault-tolerant back-stepping control method for the hypersonic flight vehicle. An adaptive law is proposed to make sure that the normal actuators could compensate the ineffective actuators while failure exists. Meanwhile, the RBF NN is employed to estimate the unknown nonlinearity of the model. The simulation results verify the effectiveness of the proposed approach.",

keywords = "Fault-tolerant control, Hypersonic flight vehicle, Neural networks",

author = "Yuyan Guo and Qiang Wang and Bin Xu",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; 3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016 ; Conference date: 19-11-2016 Through 23-11-2016",

year = "2017",

doi = "10.1007/978-981-10-5230-9\_5",

language = "英语",

isbn = "9789811052293",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "44--51",

editor = "Fuchun Sun and Huaping Liu and Dewen Hu",

booktitle = "Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers",

}

Guo, Y, Wang, Q & Xu, B 2017, Robust adaptive neural fault-tolerant control of hypersonic flight vehicle. 在 F Sun, H Liu & D Hu (版本), Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers. Communications in Computer and Information Science, 卷 710, Springer Verlag, 页码 44-51, 3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016, Beijing, 中国, 19/11/16. https://doi.org/10.1007/978-981-10-5230-9_5

Robust adaptive neural fault-tolerant control of hypersonic flight vehicle. / Guo, Yuyan; Wang, Qiang; Xu, Bin.
Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers. 编辑 / Fuchun Sun; Huaping Liu; Dewen Hu. Springer Verlag, 2017. 页码 44-51 (Communications in Computer and Information Science; 卷 710).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Robust adaptive neural fault-tolerant control of hypersonic flight vehicle

AU - Guo, Yuyan

AU - Wang, Qiang

AU - Xu, Bin

N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2017.

PY - 2017

Y1 - 2017

N2 - This paper proposes a fault-tolerant back-stepping control method for the hypersonic flight vehicle. An adaptive law is proposed to make sure that the normal actuators could compensate the ineffective actuators while failure exists. Meanwhile, the RBF NN is employed to estimate the unknown nonlinearity of the model. The simulation results verify the effectiveness of the proposed approach.

AB - This paper proposes a fault-tolerant back-stepping control method for the hypersonic flight vehicle. An adaptive law is proposed to make sure that the normal actuators could compensate the ineffective actuators while failure exists. Meanwhile, the RBF NN is employed to estimate the unknown nonlinearity of the model. The simulation results verify the effectiveness of the proposed approach.

KW - Fault-tolerant control

KW - Hypersonic flight vehicle

KW - Neural networks

UR - https://www.scopus.com/pages/publications/85026760856

U2 - 10.1007/978-981-10-5230-9_5

DO - 10.1007/978-981-10-5230-9_5

M3 - 会议稿件

AN - SCOPUS:85026760856

SN - 9789811052293

T3 - Communications in Computer and Information Science

SP - 44

EP - 51

BT - Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers

A2 - Sun, Fuchun

A2 - Liu, Huaping

A2 - Hu, Dewen

PB - Springer Verlag

T2 - 3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016

Y2 - 19 November 2016 through 23 November 2016

ER -

Robust adaptive neural fault-tolerant control of hypersonic flight vehicle

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