深海沉船燃油的回收对于海洋环境的保护具有重大意义，需要ROV对接内、外层船壳开孔机与抽液机这类大型装备来完成内、外层船板的开孔与船内抽液等一系列复杂的水下精细化作业。ROV在与大型装备对接后整个系统的动力学参数会发生较大变化，导致原控制器不再适用于新的ROV系统，在进行首向角度的控制时甚至可能发散，使得精细化作业无法进行。为此提出基于带可变遗忘因子递推最小二乘法的自校正滑模控制法，通过在线辨识变化的系统动力学参数实时更新滑模控制律，提高控制器的自适应性能，从而满足ROV协同作业的特定运动控制精度要求，并通过Matlab/Simulink首向角跟踪正弦曲线仿真实验验证了方法的有效性。
The recovery of fuel oil from deep-sea sunken ships is of great significance to the protection of the marine environment. Remote operated vehicle are required to connect large equipment such as inner and outer hull perforating machines and pumping machines to complete the perforation of the inner and outer ship plates and inner pumping and other underwater meticulous process. After the ROV is docked with large equipment, the dynamic parameters of the entire system will change significantly, resulting in the original controller being no longer suitable for the new system. It may even diverge when controlling the heading angle, making it impossible to perform meticulous process. For this reason, a self-tuning sliding mode control based on the recursive least squares method with variable forgetting factor is proposed, and the sliding mode control parameters are updated in real time through online identification of changing system dynamics parameters to improve the adaptive performance of the controller, thereby satisfying the specific motion control accuracy requirements of ROV cooperative operation, and the effectiveness of the method is verified by the simulation experiment of Matlab/Simulink heading angle tracking sine curve.
2022,44(16): 89-93 收稿日期：2021-08-07
DOI：10.3404/j.issn.1672-7649.2022.16.017
分类号：P756
基金项目：科技部支持项目(2017YFC0307002)
作者简介：李国栋(1997 - )，男，硕士研究生，主要从事水下航行器控制方面的研究
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