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.

这项工作实现了具有模型扰动和海洋扰动的水面舰艇的前导-跟随协同同步的自适应神经扰动抑制，无需先导速度测量。虚拟船减轻了对领导船速度的要求，信息要求只有领导船的位置和航向。自适应神经网络近似模型扰动。健壮项衰减神经网络逼近误差。基于自适应神经网络的干扰观测器实现了与动态表面控制技术相结合的干扰抑制。确保供应船同步控制系统实用稳定。同步控制实现船舶协同同步导航。