Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network

Zhiyuan Zhang; Cheng Zhang

doi:10.1007/978-981-97-8654-1_5

Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network

Zhiyuan Zhang, Cheng Zhang^*

^*Corresponding author for this work

School of Aerospace Engineering

Beijing Institute of Technology

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

Abstract

Aiming at the robust control problem of low static stability missiles in the process of large angle of attack flight, a robust adaptive control method based on fuzzy RBF neural network is designed. Firstly, a linear uncoupled dynamics model of a single-channel missile is established; secondly, a fuzzy RBF neural network is used to fit the dynamics model of a single-channel missile, and a control system based on the angle-of-attack feedback and acceleration feedback is designed; the stability of the control system is proved to be stable through the Lyapunov stability analysis and the tracking error is within the preset boundaries; and finally, a simulation is carried out to verify the control method. The results show that the control method based on fuzzy RBF neural network has high control accuracy, adaptability and robustness....

Original language	English
Title of host publication	Proceedings of 2024 Chinese Intelligent Systems Conference
Editors	Yingmin Jia, Weicun Zhang, Yongling Fu, Huihua Yang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	40-49
Number of pages	10
ISBN (Print)	9789819786534
DOIs	https://doi.org/10.1007/978-981-97-8654-1_5
Publication status	Published - 2024
Event	20th Chinese Intelligent Systems Conference, CISC 2024 - Guilin, China Duration: 26 Oct 2024 → 27 Oct 2024

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1284 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	20th Chinese Intelligent Systems Conference, CISC 2024
Country/Territory	China
City	Guilin
Period	26/10/24 → 27/10/24

Keywords

Adaptive control
Low static stability missile
RBF neural network

Access to Document

10.1007/978-981-97-8654-1_5

Cite this

Zhang, Z., & Zhang, C. (2024). Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network. In Y. Jia, W. Zhang, Y. Fu, & H. Yang (Eds.), Proceedings of 2024 Chinese Intelligent Systems Conference (pp. 40-49). (Lecture Notes in Electrical Engineering; Vol. 1284 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-8654-1_5

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title = "Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network",

abstract = "Aiming at the robust control problem of low static stability missiles in the process of large angle of attack flight, a robust adaptive control method based on fuzzy RBF neural network is designed. Firstly, a linear uncoupled dynamics model of a single-channel missile is established; secondly, a fuzzy RBF neural network is used to fit the dynamics model of a single-channel missile, and a control system based on the angle-of-attack feedback and acceleration feedback is designed; the stability of the control system is proved to be stable through the Lyapunov stability analysis and the tracking error is within the preset boundaries; and finally, a simulation is carried out to verify the control method. The results show that the control method based on fuzzy RBF neural network has high control accuracy, adaptability and robustness....",

keywords = "Adaptive control, Low static stability missile, RBF neural network",

author = "Zhiyuan Zhang and Cheng Zhang",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 20th Chinese Intelligent Systems Conference, CISC 2024 ; Conference date: 26-10-2024 Through 27-10-2024",

year = "2024",

doi = "10.1007/978-981-97-8654-1_5",

language = "English",

isbn = "9789819786534",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "40--49",

editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Huihua Yang",

booktitle = "Proceedings of 2024 Chinese Intelligent Systems Conference",

address = "Germany",

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Zhang, Z & Zhang, C 2024, Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network. in Y Jia, W Zhang, Y Fu & H Yang (eds), Proceedings of 2024 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol. 1284 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 40-49, 20th Chinese Intelligent Systems Conference, CISC 2024, Guilin, China, 26/10/24. https://doi.org/10.1007/978-981-97-8654-1_5

Robust Adaptive Control of Missiles Based on Fuzzy RBF Neural Network. / Zhang, Zhiyuan; Zhang, Cheng.
Proceedings of 2024 Chinese Intelligent Systems Conference. ed. / Yingmin Jia; Weicun Zhang; Yongling Fu; Huihua Yang. Springer Science and Business Media Deutschland GmbH, 2024. p. 40-49 (Lecture Notes in Electrical Engineering; Vol. 1284 LNEE).

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

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PY - 2024

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N2 - Aiming at the robust control problem of low static stability missiles in the process of large angle of attack flight, a robust adaptive control method based on fuzzy RBF neural network is designed. Firstly, a linear uncoupled dynamics model of a single-channel missile is established; secondly, a fuzzy RBF neural network is used to fit the dynamics model of a single-channel missile, and a control system based on the angle-of-attack feedback and acceleration feedback is designed; the stability of the control system is proved to be stable through the Lyapunov stability analysis and the tracking error is within the preset boundaries; and finally, a simulation is carried out to verify the control method. The results show that the control method based on fuzzy RBF neural network has high control accuracy, adaptability and robustness....

AB - Aiming at the robust control problem of low static stability missiles in the process of large angle of attack flight, a robust adaptive control method based on fuzzy RBF neural network is designed. Firstly, a linear uncoupled dynamics model of a single-channel missile is established; secondly, a fuzzy RBF neural network is used to fit the dynamics model of a single-channel missile, and a control system based on the angle-of-attack feedback and acceleration feedback is designed; the stability of the control system is proved to be stable through the Lyapunov stability analysis and the tracking error is within the preset boundaries; and finally, a simulation is carried out to verify the control method. The results show that the control method based on fuzzy RBF neural network has high control accuracy, adaptability and robustness....

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