@inproceedings{87499ad2e9554ccfb4a51c548e91e2c5,
title = "A Hybrid Network Based Disturbance Estimation Method for Stabilization Loop of Inertial Platform",
abstract = "The disturbance in the stabilization loop of the inertial platform seriously affects the system accuracy and performance. Conventional methods face challenges in identifying external disturbances. In this paper, a hybrid neural network based disturbance estimation method for inertial platform stabilization loop is proposed. The hybrid neural network model comprises a recurrent neural network (RNN) responsible for extracting local high-level disturbance features from time series, and gated recurrent units (GRU) used to compensate for global high-level disturbance features. Subsequently, these high-level features are fused and input into a fully connected layer for disturbance estimation. The effectiveness of the proposed method is verified through the stabilization loop data from the inertial platform.",
keywords = "Disturbance Estimation, Inertial Platform, Neural Network",
author = "Siqi Yang and Leilei Hao and Jiao Zhou and Zhaoxu Wang and Huiping Li",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024 ; Conference date: 08-12-2024 Through 10-12-2024",
year = "2024",
doi = "10.1109/ONCON62778.2024.10931553",
language = "英语",
series = "2024 IEEE 3rd Industrial Electronics Society Annual On-Line Conference, ONCON 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE 3rd Industrial Electronics Society Annual On-Line Conference, ONCON 2024",
}