欠驱动无人艇固定时间轨迹跟踪控制OACSTPCD

[Objectives]This study proposes a fixed-time trajectory tracking control strategy to address the challenges of unmodeled dynamics and external disturbances in underactuated unmanned surface vessels(USVs).[Methods]First,the tracking error system is divided into two channels for controller design through model transformation.Next,in order to accommodate unknown system dynamics and external disturbances,a minimum-learning-parameter-based neural network is adopted to compensate for uncertainties.After that,a fixed-time sliding mode controller is proposed with the application of a hyperbolic tangent function to ensure the fast con-vergence of tracking errors.[Results]The numerical simulation results show that fixed-time convergence for tracking errors can be guaranteed independent of the initial state.[Conclusions]The designed control scheme not only features the effective estimation of uncertainties within the system,but also demonstrates a robust disturbance rejection capability,providing valuable insights for the fixed-time control of USVs.