基于单神经元的高速列车速度跟踪控制

Speed Tracking Control for High-Speed Trains Based on Single Neuron

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.