船舶在水中航行时，所受到的水动力与船舶的运动状态之间存在着复杂的非线性关系，导致传统的线性控制方法难以取得理想的控制效果。为此，本文引入智能优化预测算法对船舶航行稳定性控制方法进行改进。首先，以航向角偏差为PID控制器输入，输出船舶舵令控制值；然后，利用智能优化预测算法中的改进野马算法优化径向基函数神经网络参数，完成水动力与船舶的运动状态之间的非线性关系线性化处理；最后，结合舵令补偿值与舵令控制值，得到最终的舵令控制值；依据最终的舵令控制值获取舵速控制指令，完成船舶的航行稳定性控制。实验证明，该方法在风速扰动与时变航向下，仍能对船舶航行稳定性进行控制，精准跟踪船舶轨迹。
There is a complex nonlinear relationship between the hydrodynamic forces experienced by a ship while navigating in water and its motion state. Traditional linear control methods are difficult to achieve ideal control effects. Therefore, this paper introduces intelligent optimization prediction algorithms to improve the ship navigation stability control method. Firstly, taking the heading angle deviation as the input of the PID controller, output the ship's rudder command control value; Then, using the improved Wild Horse algorithm in intelligent optimization prediction algorithms, the parameters of the radial basis function neural network are optimized to linearize the nonlinear relationship between hydrodynamics and the motion state of the ship; Finally, by combining the rudder compensation value with the rudder control value, the final rudder control value is obtained; Obtain rudder speed control instructions based on the final rudder command control value to complete ship navigation stability control. Experimental results have shown that this method can still control the stability of ship navigation and accurately track ship trajectories under wind speed disturbances and time-varying heading.
2025,47(8): 60-64 收稿日期：2024-7-10
DOI：10.3404/j.issn.1672-7649.2025.08.010
分类号：TP273
作者简介：柯金丁(1985-),男,讲师,研究方向为航海科学技术、航海职业教育
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