Parameter Identification of Train Basic Resistance Using Multi-Innovation Theory <ce:cross-ref refid='fn1'> <ce:sup loc='post'>?</ce:sup> </ce:cross-ref>

Xiaoyu Liu; Bin Ning; Jing Xun; Cheng Wang; Xiao Xiao; Tong Liu

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Parameter Identification of Train Basic Resistance Using Multi-Innovation Theory ?

机译：运用多元创新理论识别列车基本阻力的参数？

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Train basic resistance is important for the design of the automatic train operation, which influences the efficiency, punctuality, stop precision, energy consumption, and the safety of the train. The multi-innovation theory is a novel concept which can improve the accuracy of parameter estimation and be used to modify the traditional recursive least squares algorithm. In this paper, we derive the regularization form of the multi-innovation least squares algorithm and apply it to the train basic resistance parameter estimation. The simulation results based on the Yizhuang Line of Beijing Subway indicate that, compared with traditional least squares algorithm, the multi-innovation least squares algorithm can provide higher estimation accuracy and robustness, and can be used for online identification.

机译：列车基本阻力对于自动列车运行的设计很重要，它会影响效率，准时性，停车精度，能耗和列车安全性。多元创新理论是一个新颖的概念，可以提高参数估计的准确性，并可以用来修改传统的递归最小二乘算法。本文推导了多元创新最小二乘算法的正则化形式，并将其应用于列车基本阻力参数估计。基于北京地铁亦庄线的仿真结果表明，与传统的最小二乘算法相比，多元创新的最小二乘算法具有更高的估计精度和鲁棒性，可用于在线辨识。

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来源
《IFAC PapersOnLine》 |2018年第18期|共6页
作者
Xiaoyu Liu; Bin Ning; Jing Xun; Cheng Wang; Xiao Xiao; Tong Liu;
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中图分类自动化技术、计算机技术;
关键词
Train basic resistanceMulti-innovation identificationRecursive identificationParameter estimationUrban rail transit;

机译：列车基本阻力多次创新识别递归识别参数估计城市轨道交通;

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Parameter Identification of Train Basic Resistance Using Multi-Innovation Theory ?

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