Abstract: This paper proposes a dynamic response optimization algorithm for boarding equipment on floating offshore wind turbine foundations, to address the problems of large control delay and low control accuracy in the dynamic response of offshore boarding equipment under harsh sea conditions. Capacitive acceleration sensors are deployed on the boarding equipment to monitor the displacement amplitude under multi-degree-of-freedom motion response. The water level allocation problem of the ballast tank is transformed into a mathematical optimization model with the objective of minimizing the displacement difference at each monitoring point, and is solved using the Harris Hawks optimizer (HHO) to obtain the optimal water level allocation scheme. An improved PID controller is adopted to accurately track the water level allocation scheme, and the water pumps dynamically adjust the inflow or outflow of the ballast tank to actively suppress the motion of the boarding equipment. Experimental results show that this method can significantly reduce the motion difference between each position point, decreasing the maximum displacement error from 1.33 m to 0.20 m. Under extreme sea conditions, the dynamic response delay is only 0.5 s and the overshoot is small (fluctuating around 0.3%), demonstrating that the algorithm can maintain the stability of the boarding equipment more quickly and accurately, effectively improving the safety of boarding operations.

Key words: floating offshore wind turbine boarding equipment, dynamic response optimization, ballast tank water level adjustment, Harris Hawks optimizer (HHO), PID control

摘要： 针对恶劣海况导致海上登乘的动态响应控制延迟大、控制精度低的问题,该文提出一种针对漂浮式海上风电基础登乘设备的动态响应优化算法。该算法在登乘设备上部署电容式加速度传感器,以监测其多自由度运动响应下的位移幅值;将压载舱水位分配问题转化为一个以最小化各监测点位移差值为目标的数学优化模型,并利用哈里斯鹰算法求解,以获得最优水位分配方案。采用改进PID控制器精确跟踪水位分配方案,并通过水泵动态调节压载舱进水或出水,以主动抑制登乘设备运动。实验结果表明：该方法能显著降低各位置点间的运动差异,将最大位移误差从1.33 m降至0.20 m;在极端海况下,该算法动态响应延迟仅0.5 s,超调量小（波动幅度约0.3%）,证明其能够更快速、精准地维持登乘设备稳定,有效提升登乘作业的安全性。

关键词: 漂浮式海上风电登乘设备, 动态响应优化, 压载舱水位调节, 哈里斯鹰优化算法, PID控制