摘要
列车自动驾驶成为近年来的研究热点,其中的速度精准控制与跟踪性能仍需进一步研究与改善,为此采用单神经元对列车速度实施控制。首先阐述单质点列车模型,研究单神经元控制算法。然后设计列车速度跟踪控制系统,该系统采用非线性反馈闭环控制结构,它能实时产生列车所需的牵引力和制动力。最后在计算机上进行仿真研究,并比较三种方法的仿真结果。仿真实验表明,单神经元控制具有跟踪误差小、响应时间短、结构简单等优势。
Automatic train operation has become a research hotspot in recent years,and the precise speed control,as well as tracking performance,needs to be further studied and improved.Thus,the paper uses a single neuron to control the train speeds.Firstly,a single-particle train model is formulated,and the control algorithm of a single neuron is studied.Then the train control system for speed tracking is designed.This system utilizes a closed-loop control structure with nonlinear feedback,and it can produce the required traction force and braking force in real-time.Finally,simulation studies are conducted on a computer,and simulation results of three methods are compared.Simula⁃tion experiments prove that the single neuron control has such advantages as small tracking error,short response time,and simple control structure.
作者
王雪奇
莫晓婷
梁新荣
董超俊
WANG Xue-qi;MO Xiao-ting;LIANG Xin-rong;DONG Chao-jun(Department of Traffic Engineering,Faculty of Intelligent Manufacturing,Wuyi University,Jiangmen 529020)
出处
《现代计算机》
2021年第1期12-15,38,共5页
Modern Computer
基金
广东省科技计划项目(No.2017A010101019)
广东省大学生创新创业训练项目(2020年立项)。
关键词
高速列车
速度控制
单神经元
非线性反馈
High-Speed Train
Speed Control
Single Neuron
Nonlinear Feedback