This article is dedicated to solving the problem of predefined-time cooperative control for autonomous surface vessels encountering model uncertainties and external perturbations. By virtue of the prescribed-time stable theory, a robust formation controller is constructed, with which the settling time of the cooperative system can be prescribed in advance. The controller is developed under the backstepping framework, where the dynamic surface control is applied to generate the real-time command. Considering the unmodeled autonomous surface vessel dynamics, the neural network-based nonlinear approximator is incorporated with minimum-learning-parameter technique. Under this scenario, the real-time control can be pursed with one parameter being estimated. Finally, comparative simulation examples are provided to exhibit the effectiveness and advantages of designed control strategies.

本文致力于解决自主水面舰艇遇到模型不确定性和外部扰动时的预定义时间协同控制问题。利用规定时间稳定理论，构建了一个鲁棒编队控制器，可以预先规定协同系统的建立时间。该控制器是在反推框架下开发的，其中应用动态表面控制来生成实时命令。考虑到未建模的自主水面舰艇动力学，基于神经网络的非线性逼近器与最小学习参数技术相结合。在这种情况下，可以通过估计一个参数来进行实时控制。最后，