欠驱动无人艇固定时间轨迹跟踪控制

Fixed-time trajectory tracking control for underactuated surface vessels

  • 摘要:
    目的 针对欠驱动无人艇系统内部存在模型参数不确定以及外部受到未知干扰等问题,提出一种具有抗干扰能力的固定时间轨迹跟踪控制策略。
    方法 首先,通过模型转换将跟踪误差系统分为2个子系统,分别开展控制器设计;然后,为解决系统内外的未知干扰问题,基于径向基神经网络和最小参数学习法对不确定项进行估计,从而保证系统具有抗干扰能力;最后,将双曲正切函数与滑模控制相结合,提出一种基于固定时间的跟踪控制方法,以保证无人艇可在固定时间内快速跟踪期望轨迹。
    结果 仿真结果表明,跟踪误差可在固定时间内实现收敛并保持稳定,且其收敛时间与初始状态无关。
    结论 该控制策略可对系统中的不确定项进行有效估计,具有良好的抗干扰能力,可为欠驱动无人艇的固定时间控制提供参考。

     

    Abstract:
    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 convergence 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.

     

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