Adaptive Iterative Learning Control for High-Speed Trains With Unknown Speed Delays and Input Saturations

被引：176

作者：

Ji, Honghai ^{[1
]}

Hou, Zhongsheng ^{[1
]}

Zhang, Ruikun ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Adv Control Syst Lab, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

来源：

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING | 2016年 / 13卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Adaptive iterative learning control; composite energy function; input saturations; time-varying speed delays; highspeed train; train control; NONLINEARLY PARAMETERIZED SYSTEMS; ENERGY-CONSUMPTION; CRUISE CONTROL; TIME; FEEDBACK; DESIGN; MODEL;

D O I：

10.1109/TASE.2014.2371816

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, an adaptive iterative learning control (AILC) strategy for high-speed trains with unknown speed delays and control input saturations is designed to address speed trajectory tracking problem. The train motion dynamics containing nonlinearities and parametric uncertainties are formulated as a nonlinearly parameterized system. Instead of estimation or modeling of train delays, an unknown time-varying delay term is integrated into the speed on delay analysis by means of Lyapunov-Krasovskii function. Through rigorous analysis, it is confirmed that the proposed AILC mechanism can guarantee convergence of train speed to the desired profile during operations repeatedly. Case studies with numerical simulations further verify the effectiveness of the proposed approach.

引用

页码：260 / 273

页数：14

共 44 条

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