水下无人系统学报2024，Vol.32Issue(2)：311-319,9.DOI:10.11993/j.issn.2096-3920.2023-0033
基于RBF神经网络补偿的ROV运动控制算法
ROV Motion Control Algorithm Based on RBF Neural Network Compensation
摘要
Abstract
In view of the motion control problem of the operation-type remotely operated vehicles(ROVs)under the uncertainty of model parameters and the disturbance of the external environment,an adaptive double-loop sliding mode control strategy based on radial basis function(RBF)neural network was proposed.Firstly,the integral sliding mode control method with an improved reaching law was adopted for controlling the position of the ROV's outer loop,and the integral sliding mode control method with an exponential reaching law was adopted for controlling the speed of the ROV's inner loop.Secondly,in order to further improve the chattering problem of sliding mode control,the hyperbolic tangent function was introduced as the sliding mode switching term.Subsequently,the RBF neural network control technology was used to estimate and compensate for the uncertain parameters and external disturbances of the ROV model.Finally,the stability of the whole closed-loop system was proved by using the Lyapunov stability theory,and the motion control of the operation-type ROV was simulated numerically.The simulation results verify that the controller designed in this paper can achieve precise control of ROV navigation and effectively suppress the influence of uncertain parameters of the model and external disturbances on ROV motion.关键词
遥控水下航行器/运动控制/径向基函数/自适应双环滑模控制/神经网络Key words
remotely operated vehicle/motion control/radial basis function/adaptive double-loop sliding mode control/neural network分类
军事科技引用本文复制引用
张帅军,刘卫东,李乐,柳靖彬,郭利伟,徐景明..基于RBF神经网络补偿的ROV运动控制算法[J].水下无人系统学报,2024,32(2):311-319,9.基金项目
国家自然科学基金(61903304) （61903304）
中央高校基本科研业务费项目(3102020HHZY030010) （3102020HHZY030010）
"111"引智计划项目(B18041.0). （B18041.0）
