中文摘要：

为实现水下航行器的精准航迹跟踪控制,设计一种基于动态趋近律和动态模糊神经网络的控制方法.在动态趋近律滑模控制框架下,提出一种依据模糊激活度增加或减少模糊规则的动态模糊神经网络,用于在线逼近系统不确定性和时变干扰的集总项.通过Lyapunov稳定性理论分析可知,所提策略可保证闭环系统的稳定性及所有信号的有界性,同时跟踪误差及其导数渐进趋向于零.仿真实验结果表明,该策略可有效处理系统不确定性并抑制外界时变干扰的影响,实现水下无人航行器的精确航迹跟踪控制.

英文摘要：

To achieve high-accuracy trajectory tracking control of underwater vehicles with system uncertainties and external disturbances,a novel approach based on dynamic reaching law and fuzzy neural network was proposed,where the dynamic fuzzy neural network was developed to online approximate the lumped term of uncertainties and time-varying disturbances,which dynamically generates and prunes fuzzy rules based on the fuzzy firing strength. Lyapunov stability analysis proves that the proposed scheme can guarantee the stability of closed-loop system and the boundedness of all signals. In addition,the tracking errors and derivative are asymptotically converge to zero. Simulation results demonstrate that the proposed scheme is able to cope with the system uncertainties and external time-varying disturbances, and achieve trajectory tracking of underwater vehicles with high accuracy.