Non-material state estimation of arresting cable based on ALE formulation and UKF

Haiming Lei; Huan Zhang; Yue Hou; Tianci Zhang; Zhiquan Kong

doi:10.1117/12.2684928

19 October 2023 Non-material state estimation of arresting cable based on ALE formulation and UKF

Haiming Lei, Huan Zhang, Yue Hou, Tianci Zhang, Zhiquan Kong

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127094Z (2023) https://doi.org/10.1117/12.2684928
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

This paper considers the problem that a sensor cannot directly obtain the arresting point status information of the arresting cable during the shipborne Unmanned Aerial Vehicle (UAV) cable-hock recovery process. To overcome this consideration, this study proposes an observation method based on Arbitrary Lagrangian Eulerian (ALE) formulation and Unscented Kalman Filter (UKF) for the non-material point status of the moving arresting cable. Specifically, the ALE method is used to model the dynamics of the arresting cable. Besides, the traditional Kalman filtering algorithm is employed, and the backward difference method is combined with UKF to estimate the vertical displacement of the arresting point on the arresting cable. Extensive simulations demonstrate that the proposed method accurately estimates the dynamic parameters of the arresting point in the arresting cable and achieves accurate state estimation of the carrier-based UAV recovery arresting cable.

Citation Download Citation

Haiming Lei, Huan Zhang, Yue Hou, Tianci Zhang, and Zhiquan Kong "Non-material state estimation of arresting cable based on ALE formulation and UKF", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127094Z (19 October 2023); https://doi.org/10.1117/12.2684928

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