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  4. Vol 5, Issue 2, 2024

Trajectory Tracking Control of Unmanned Surface Vessel Based on Neural Network Observer

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DOI: 10.23977/autml.2024.050210 | Downloads: 23 | Views: 634

Author(s)

Ang Zheng 1, Junhan Yang 2, Xiaoming Xia 2

Affiliation(s)

1 Makarov College of Marine Engineering, Jiangsu Ocean University, Lianyungang, Jiangsu, China
2 College of Marine Engineering, Jiangsu Ocean University, Lianyungang, Jiangsu, China

Corresponding Author

Ang Zheng

ABSTRACT

In this paper, we propose a trajectory tracking control scheme for unmanned ships based on neural network observers, which has model uncertainty, unknown environmental disturbance and saturation problems. A neural network-based observer was developed to reconstruct unmeasured velocity and estimate the uncertainty of the model. Using the neural network, a neural adaptive output feedback controller was developed. In addition, a stable controller was designed by the backstepping method. Finally, the Lyapunov analysis shows that all signals in the closed-loop system are bounded. The feasibility of the proposed control scheme is verified by simulation.

KEYWORDS

Neural network state observer, Unmanned ship motion control, uncertain term, Lyapunov function

CITE THIS PAPER

Ang Zheng, Junhan Yang, Xiaoming Xia, Trajectory Tracking Control of Unmanned Surface Vessel Based on Neural Network Observer. Automation and Machine Learning (2024) Vol. 5: 86-96. DOI: http://dx.doi.org/10.23977/autml.2024.050210.

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