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Automatic Control and Computer Sciences

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01-06-2023

Spatial Adaptive Iterative Learning Control Based High-Speed Train Operation Tracking under External Disturbance

Authors: Zhang Xin, Zhu Zijun

Published in: Automatic Control and Computer Sciences | Issue 3/2023

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Abstract

In order to solve the trajectory tracking problem of high-speed train automatic operation systems under external random disturbance, the temporal train aerodynamic model is transformed into a spatial train model by using the spatial differentiator. Firstly, this paper proposes a spatial adaptive learning control (SAILC) algorithm based on the recursive least square (RLS) algorithm to identify parameters and learn the repetitive information of the system, so as to drive the train to automatically track the desired speed trajectory. Secondly, the spatial composite energy function (SCEF) based on Lyapunov is established, and its differential negative definiteness and boundedness are proved. Finally, the proposed SAILC algorithm is compared with an iterative learning control algorithm. The results show that the proposed algorithm has better performance on convergence speed and anti-interference capability.

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Title: Spatial Adaptive Iterative Learning Control Based High-Speed Train Operation Tracking under External Disturbance
Authors: Zhang Xin
Zhu Zijun
Publication date: 01-06-2023
Publisher: Pleiades Publishing
Published in: Automatic Control and Computer Sciences / Issue 3/2023
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411623030094

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