运行时间区间可变的地铁列车无模型自适应迭代学习控制  

Model-free adaptive iterative learning control for subway train with variable operation time interval

作　　者：焦世广 侯忠生 JIAO Shi-guang;HOU Zhong-sheng(College of Automation,Qingdao University,Qingdao Shandong 266071,China)

机构地区：[1]青岛大学自动化学院,山东青岛266071

出　　处：《控制理论与应用》2025年第3期642-648,共7页Control Theory & Applications

摘　　要：针对地铁列车系统非严格重复运行的特性,提出了一种运行时间区间可变的地铁列车无模型自适应迭代学习控制算法.首先,利用紧格式动态线性化方法将地铁列车动力学模型转化为等价的数据模型;其次,仅利用系统输入/输出数据设计了一种适用于地铁列车迭代时间长度随机变化的改进无模型自适应迭代学习控制算法;最后,给出了该算法的收敛性分析,并通过仿真验证了所提算法的有效性.For the characteristics of non-strict repetitive operation of subway train,a model-free adaptive iterative learning control algorithm for subway trains with variable operation time interval is proposed.Firstly,the compact format dynamic linearization method is used to convert the subway train dynamics model into an equivalent data model;Secondly,an improved model free adaptive iterative learning control algorithm for the random change of subway train iterative time length is designed using only the input/output data of train system.Finally,the convergence analysis of the proposed algorithm is presented,and the effectiveness of the proposed algorithm is verified through simulation.

关 键 词：地铁列车 无模型自适应控制 无模型自适应迭代学习控制 迭代时间区间随机变化 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]