拖曳式ROV在进行拖曳作业时类似于深海拖曳系统，受限于声学探测设备的要求，拖曳作业时需要对拖曳式ROV的深度进行精确的控制，而传统的深度控制方法控制效果较差。为此提出一种基于粒子群算法优化的拖曳式ROV深度自抗扰控制方法（PSO-ADRC），使用PSO-ADRC算法控制绞车收放缆进而控制拖曳式ROV的拖曳深度。仿真结果表明，PSO-ADRC算法在拖曳式ROV的深度控制中具有动态响应快、稳态精度高、抗干扰能力强的优点，简化了调参过程，为实际应用提供借鉴。
The towed ROV is similar to the deep towing system when carrying out towing operations, but it is limited by the requirements of acoustic detection equipment, and the depth of the towed ROV needs to be accurately controlled during towing operations, while the traditional depth control method has poor control effect. Therefore, a towed ROV depth active disturbance rejection control method (PSO-ADRC) based on particle swarm optimization was proposed, and the PSO-ADRC algorithm was used to control the winch retracting and unwinding cables to control the towing depth of the towed ROV. The simulation results show that the PSO-ADRC algorithm has the advantages of fast dynamic response, high steady-state accuracy and strong anti-interference ability in the depth control of towed ROV, which simplifies the parameter tuning process and provides reference for practical application.
2025,47(18): 75-81 收稿日期：2024-10-11
DOI：10.3404/j.issn.1672-7649.2025.18.013
分类号：U665.13
作者简介：孙元昊（1998 – ），男，硕士，研究方向为水下机器人技术
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