Adaptive neural network control of zero speed ship rolling motion based on state observer

Jing He; Ziteng Sun; Cheng Li

doi:10.1117/12.2681273

23 May 2023 Adaptive neural network control of zero speed ship rolling motion based on state observer

Jing He, Ziteng Sun, Cheng Li

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126452B (2023) https://doi.org/10.1117/12.2681273
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

In this paper, an adaptive neural network control method based on state observers is proposed for the rolling motion control problem of zero-speed ships. By combining the neural network with the disturbance observer technique, the internal and external uncertainties of the rolling motion control system of zero-speed ships are overcome. Considering that the ship's rolling angular velocity is difficult to be measured accurately under the actual sea state, the state observer is introduced to estimate the unknown rolling angular velocity. Finally, the simulation results verify the effectiveness of the control scheme.

Citation Download Citation

Jing He, Ziteng Sun, and Cheng Li "Adaptive neural network control of zero speed ship rolling motion based on state observer", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126452B (23 May 2023); https://doi.org/10.1117/12.2681273

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