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Adaptive synchronization of marine surface ships using disturbance rejection without leader velocity
Xin Hu1, Xinjiang Wei1, Qingtao Gong2
1School of Mathematics and Statistics Science, Ludong University, Yantai, Shandong, 264025, PR China.
Abstract:
This work realizes the adaptive neural disturbance rejection for the leader-follower cooperative synchronization of surface ships with model perturbations and ocean disturbances without leader velocity measurements. The virtual ship alleviates the requirements on leader ship's velocities such that the information requirements are only position and heading on the leader ship. The adaptive neural networks approximate model perturbations. The robustifying term attenuates neural network approximation errors. The adaptive neural network-based disturbance observer achieves the disturbance rejection which is integrated with the dynamic surface control technique. The supply ship synchronization control system is ensured to be practical stable. The synchronization control realizes the ship's cooperative synchronization navigation. Simulations with comparisons validate the synchronization scheme.
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