Adaptive neural sliding mode control for heterogeneous ship formation keeping considering uncertain dynamics and disturbances

Journal Article (2022)
Author(s)

Xu You (Wuhan University of Technology)

Xinping Yan (Wuhan University of Technology)

Jialun Liu (Wuhan University of Technology)

Shijie Li (Wuhan University of Technology)

R Negenborn (TU Delft - Transport Engineering and Logistics)

Research Group
Transport Engineering and Logistics
Copyright
© 2022 Xu You, Xinping Yan, Jialun Liu, Shijie Li, R.R. Negenborn
DOI related publication
https://doi.org/10.1016/j.oceaneng.2022.112268
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Xu You, Xinping Yan, Jialun Liu, Shijie Li, R.R. Negenborn
Research Group
Transport Engineering and Logistics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Volume number
263
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Abstract

This paper investigates the formation keeping problem of heterogeneous ships with underactuated inputs, uncertain dynamics, and environmental disturbances. The control objective is to make the heterogeneous followers keep the desired formation while tracking a leader. To solve the problem effectively, a novel virtual leader–follower formation scheme considering the ship heterogeneity is proposed by utilizing the backstepping method, adaptive neural network, and adaptive control law. The stability of the formation control system is proved based on Lyapunov's direct method where all tracking errors are guaranteed to be uniformly ultimately bounded. Finally, simulations and comparisons are conducted to verify the effectiveness of the proposed control law.

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