水下无人系统学报2025，Vol.33Issue(1)：37-45,9.DOI:10.11993/j.issn.2096-3920.2024-0045
海流扰动下ROV自适应神经网络控制
Adaptive Neural Network Control of ROVs under Ocean Current Disturbance
摘要
Abstract
In view of the motion control problem of remotely operated vehicles(ROVs)under uncertain model parameters and ocean current disturbance,an adaptive back-stepping control system was designed based on the limited time command filtering and radial basis function(RBF)neural network.Firstly,a stochastic ocean current model based on the Markov process was constructed,and an ROV mathematical model under ocean current disturbance was established.Secondly,command filtering technology was introduced for the desired velocity to reduce the amount of calculation caused by the iterative derivative of the traditional back-stepping method.Thirdly,the RBF neural network was utilized to estimate the uncertainty terms and external unknown disturbances of the ROV model,and an adaptive neural network controller was designed.Finally,the Lyapunov stability theory was used to prove the stability of the closed-loop control system.The simulation results show that the controller designed in this paper can achieve precise control of ROV navigation and effectively suppress the impact of uncertainty term of the model and ocean current disturbance on ROV motion.关键词
水下遥控机器人/海流扰动/命令滤波/径向基函数神经网络Key words
remotely operated vehicle/ocean current disturbance/command filtering/radial basis function neural network分类
武器工业引用本文复制引用
李相衡,闫昭琨,楼建坤,王鸿东..海流扰动下ROV自适应神经网络控制[J].水下无人系统学报,2025,33(1):37-45,9.基金项目
国家自然科学基金面上项目(52271348). （52271348）
