摘要
高速列车运行速度快,运行过程复杂,具有较强的非线性,难以实现高精度速度跟踪控制.为了实现高速列车的安全可靠运行,本文研究提出高速列车的运行过程建模和速度跟踪控制方法,采用数据驱动建模方法建立了高速列车运行过程Elman模型,设计了改进型广义预测控制实现了高速列车速度跟踪控制.基于CRH380AL运行过程数据的仿真结果表明,该方法具有更高的跟踪控制精度和较强的鲁棒性,可实现高速列车安全、正点运行.
High-speed trains have high running speed, complex operation process and strong nonlinearity, which make difficulty for their high-precision modeling and control. To guarantee the safety of the high-speed trains' running process,this paper presents a modeling method and a speed tracking control scheme for their running process. A method of datadriven modeling is employed to establish the Elman model for the running process of the high-speed train, and a modified generalized predictive control algorithm is used to develop a speed tracking controller to realize the speed tracking. The simulation results based on the CRH380 AL operation process data indicate that the method presented in the paper can realize the safe and accurate running of high-speed trains, and the method makes higher precision and higher robustness.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2017年第1期125-130,共6页
Control Theory & Applications
基金
国家自然科学基金项目(61673172
61663013
U1334211)
流程工业综合自动化国家重点实验室开放课题(PAL–N201501)资助~~
关键词
高速列车
系统辨识
广义预测控制
ELMAN神经网络
数据驱动
high-speed train
system identification
generalized predictive control
Elman neural network
data-driven