无人船自适应超螺旋轨迹跟踪滑模控制

Adaptive super-twisting trajectory tracking sliding mode control for unmanned surface vessel

针对无人船受到风浪等不确定性干扰时易出现轨迹跟踪误差大、自适应增益范围小、滑模控制方法的抖振等问题,提出了一种新型自适应超螺旋滑模控制算法。根据无人船结构建立数学模型,引入轨迹参考点将数学模型转换为二阶系统微分方程;设计自适应超螺旋滑模控制器;构造Lyapunov函数,推导满足系统闭环稳定性的自适应增益。在考虑风阻、浪阻的情况下,将本文方法分别与超螺旋滑模控制和传统自适应超螺旋滑模控制这两种方法进行仿真实验对比。结果显示,在仿真实验的30 s中,本文方法的轨迹跟踪平均绝对误差比超螺旋滑模控制和传统自适应超螺旋滑模控制分别减少了0.60 m和0.27 m,仿真结果表明本文方法能够有效提高系统控制性能,抑制抖振,减小轨迹跟踪误差。

This paper addresses challenges in unmanned surface vessel(USV)trajectory tracking,such as significant errors induced by wind and waves,limited adaptability of adaptive gains,and vibrations in sliding mode control.A novel adaptive Super-Twisting sliding mode control algorithm is proposed to mitigate these issues.The USV mathematical model,derived from its structure,is transformed into a second-order system differential equation using trajectory reference points.An adaptive Super-Twisting sliding mode controller is designed,and adaptive gains ensuring closed-loop system stability are derived through the construction of a Lyapunov function.Simulation experiments,considering wind and wave resistance,compare the proposed method with Super-Twisting sliding mode control and traditional adaptive Super-Twisting sliding mode control.Results demonstrate a reduction in average tracking errors of 0.60 m and 0.27 m,respectively,over a 30-second simulation period,affirming the effectiveness of the proposed method in enhancing system control performance,suppressing vibrations,and reducing trajectory tracking errors.