本文研究了在环境扰动和执行器饱和影响下，受到状态约束的动力定位（Dynamic Positioning, DP）船的轨迹跟踪问题。首先，针对未知环境扰动的影响，构造了一种基于积分滑模和固定时间控制的连续固定时间扰动观测器（Fixed-time Disturbance Observer, FTDO）。其次，采用带辅助变量的抗饱和补偿器来处理指令控制力和实际控制力之间不一致的问题。再次，基于tan型障碍李雅普诺夫函数（Barrier Lyapunov Function, BLF）和神经网络（Radial Basis Function Neural Network, RBFNN）开发了一种具有状态约束的自适应控制律来跟踪期望轨迹。最后，通过仿真验证了提出的DP船观测器和控制器的有效性。
In this paper, the trajectory tracking problem of dynamic positioning (DP) ship subject to state constraints is studied under the influence of environmental disturbance and actuator saturation. Firstly, a fixed-time disturbance observer (FTDO) based on integral sliding mode and fixed time control is constructed to deal with the influence of unknown environment disturbance. Secondly, an anti-saturation compensator with auxiliary variables is used to deal with the inconsistency between the command control force and the actual control force. Third, based on the tan-type barrier Lyapunov function (BLF) and Radial Basis Function Neural Network (RBFNN) an adaptive control law with state constraints is proposed to track the desired trajectory. Finally, the effectiveness of the proposed DP ship observer and controller is verified by simulation.
2024,46(16): 43-50 收稿日期：2023-07-06
DOI：10.3404/j.issn.1672-7649.2024.16.008
分类号：U675.73
作者简介：范锦宇（1999 – ），男，硕士研究生，研究方向为无人船航行控制
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