This article focuses on the problem of path following for underactuated unmanned surface vehicles (USVs) considering model uncertainties and time-varying ocean currents. An extended state observer (ESO)-based integral line-of-sight (ILOS) with an integral sliding mode adaptive fuzzy control scheme is proposed as the main control framework. First, a novel ESO is employed to estimate the surge and sway velocities based on the kinetic model, which are difficult to measure directly. Then, the adaptive ILOS guidance law is proposed, in which the integral vector is incorporated into the adaptive method to estimate the current velocities. Meanwhile, an improved fuzzy algorithm is introduced to optimize the look-ahead distance. Second, the controller is extended to deal with the USV yaw and surge velocity signal tracking using the integral sliding mode technique. The uncertainties of the USV are approximated via the adaptive fuzzy method, and an auxiliary dynamic system is presented to solve the problem of actuator saturation. Then, it is proved that all of the error signals in the closed-loop control system are uniformly ultimately bounded. Finally, a comparative simulation substantiates the availability and superiority of the proposed method for ESO-based ILOS path following of USV.

本文重点关注考虑模型不确定性和时变海流的欠驱动无人水面载具（USV）的路径跟踪问题。提出了一种基于扩展状态观测器（ESO）的具有集成滑模自适应模糊控制方案的集成视线（ILOS）作为主控制框架。首先，采用一种新颖的ESO来基于动力学模型估算喘振和摇摆速度，这是很难直接测量的。然后，提出了自适应的ILOS制导律，其中将积分矢量合并到自适应方法中以估计当前速度。同时，引入了一种改进的模糊算法来优化超前距离。第二，控制器扩展为使用积分滑模技术处理USV偏航和喘振速度信号跟踪。USV的不确定性通过自适应模糊方法进行近似，并提出了一种辅助动力系统来解决执行器饱和问题。然后，证明了闭环控制系统中的所有误差信号最终均一地受到限制。最后，比较仿真证实了所提方法在基于ESO的USV ILOS路径跟踪中的有效性和优越性。