针对船舶模型不确定和控制增益未知的非线性船舶航向控制问题,基于RBF神经网络自适应控制,提出一种新的非线性航向保持控制器.首先,在理论上证明存在连续的控制律;然后,通过RBF神经网络对其逼近;最后,借助Lyapunov稳定性理论分析证明船舶航向保持闭环系统的所有误差信号一致最终有界.仿真研究验证了该控制器的有效性. Aiming at the nonlinear heading control problem with uncertain ship model and unknown control gain, a new nonlinear heading control controller based on RBF neural network adaptive control is proposed. Firstly, it is proved theoretically that there is a continuous control law; then , Which is approximated by RBF neural network. Finally, with the aid of Lyapunov stability theory, it is proved that all error signals of the ship heading-keeping closed-loop system are uniformly and ultimately bounded. Simulation results show the effectiveness of this controller.