Fault Reconstruction Method of Neural Network Observer Group for High-Speed Vehicle

Cong Li, Yibo Ding, Cheng Bi, Xiaokui Yue, Yuhao Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Aiming at the actuator failure of the attitude control system for high-speed vehicle, a fault reconstruction method of observer group based on neural network classifier is introduced. Firstly, the model of the vehicle and the failure model are established. Secondly, a dataset that represents the characteristics of step and sinusoidal fault information is established, which is used to train neural networks in order to classify fault information. Then, according to the classification results, appropriate observers related to distinct fault types for fault reconstruction are selected. For the purpose of solving the problem that different fault types have different performance requirements for observers, an observer group which contains a high-order sliding mode observer and an iterative learning observer is proposed. It can meet high accuracy requirements of step-form faults and fast response requirements of sinusoidal-form faults, so as to realize higher effective fault reconstruction. The classification fault reconstruction method can achieve excellent estimation of angular velocity and fault value. At last, the efficiency of the introduced method is verified by simulation.

源语言英语
主期刊名Advances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 8
编辑Liang Yan, Haibin Duan, Yimin Deng
出版商Springer Science and Business Media Deutschland GmbH
292-301
页数10
ISBN(印刷版)9789819622276
DOI
出版状态已出版 - 2025
活动International Conference on Guidance, Navigation and Control, ICGNC 2024 - Changsha, 中国
期限: 9 8月 202411 8月 2024

出版系列

姓名Lecture Notes in Electrical Engineering
1344 LNEE
ISSN(印刷版)1876-1100
ISSN(电子版)1876-1119

会议

会议International Conference on Guidance, Navigation and Control, ICGNC 2024
国家/地区中国
Changsha
时期9/08/2411/08/24

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