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

School of Automation

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers
Editors	Fuchun Sun, Huaping Liu, Dewen Hu
Publisher	Springer Verlag
Pages	44-51
Number of pages	8
ISBN (Print)	9789811052293
DOIs	https://doi.org/10.1007/978-981-10-5230-9_5
State	Published - 2017
Event	3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016 - Beijing, China Duration: 19 Nov 2016 → 23 Nov 2016

Publication series

Name	Communications in Computer and Information Science
Volume	710
ISSN (Print)	1865-0929

Conference

Conference	3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016
Country/Territory	China
City	Beijing
Period	19/11/16 → 23/11/16

Keywords

Fault-tolerant control
Hypersonic flight vehicle
Neural networks

Access to Document

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

Cite this

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

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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",

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Guo, Y, Wang, Q & Xu, B 2017, Robust adaptive neural fault-tolerant control of hypersonic flight vehicle. in F Sun, H Liu & D Hu (eds), Cognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers. Communications in Computer and Information Science, vol. 710, Springer Verlag, pp. 44-51, 3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016, Beijing, China, 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. ed. / Fuchun Sun; Huaping Liu; Dewen Hu. Springer Verlag, 2017. p. 44-51 (Communications in Computer and Information Science; Vol. 710).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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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

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KW - Neural networks

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A2 - Sun, Fuchun

A2 - Liu, Huaping

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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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Keywords

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