现代信息科技2024，Vol.8Issue(8)：83-88,6.DOI:10.19850/j.cnki.2096-4706.2024.08.019
基于实时反馈强化学习神经网络的船舶艏摇智能控制研究
Research on Intelligent Control of Ship Yaw Based on Real-time Feedback Reinforcement Learning Neural Network
摘要
Abstract
This paper proposes an intelligent control method for ship yaw based on real-time feedback reinforcement learning neural network control.This method combines nonlinear modeling of neural networks with adaptive control technology of reinforcement learning to achieve precise control of rudder angle during ship navigation.And the PID control algorithm,model prediction control algorithm,and real-time feedback reinforcement learning neural network control algorithm are compared and analyzed.The simulation experiment results show that the latter is superior to the previous two methods in control effectiveness and stability,and could effectively improve the control accuracy and robustness of the rudder angle during ship navigation.关键词
实时反馈/强化学习/神经网络/船舶艏摇Key words
real-time feedback/reinforcement learning/neural network/ship yaw分类
信息技术与安全科学引用本文复制引用
宋伟伟,徐跃宾,段学静,巩方超,崔英明..基于实时反馈强化学习神经网络的船舶艏摇智能控制研究[J].现代信息科技,2024,8(8):83-88,6.基金项目
山东省船舶控制工程与智能系统工程技术研究中心科研专项(SSCC-2021-0006) （SSCC-2021-0006）
