高速列车隧道压力波模拟迭代遗忘因子控制

Iterative Learning Control of the High-speed Train Tunnel Pressure Wave Simulation System with Forgetting Factor

高速列车在隧道运行、隧道交会时车内、外会产生交替变化的气压差,对车体气密性及材料耐疲劳强度提出更高要求。基于Matlab和AMESim构建联合仿真平台,设计高速列车隧道压力波模拟系统。使用实测隧道压力波数据作为期望输出,研究车体气密疲劳性能。考虑到模拟系统非线性、大时滞及多扰动特点,采用一种带有时变遗忘因子的开环迭代PID控制算法。仿真结果表明,其系统更稳定、收敛速度更快。

When high-speed trains is running or pass by each other in a tunnel, alternating pressure differences will form, which will put forward more requirements about air tightness and fatigue strength of a car body. Based on Matlab and AMESim, this paper establishes a union simulation platform in order to design the tunnel pressure wave simulation system of the high-speed train. The actual measuring tunnel pressures are acted as expectations. It would bring convenience to the research of the air tightness and fatigue capability of a car body. Considering its nonlinearity, large time-delay and multiple disturbances, an open PID iterative learning control algorithm with forgetting factors for time is used in the pressure control. The simulation results show that the system has better stability and faster convergence speed.