Adaptive polynomial approximation-based virtual coupled cooperative control for high-speed trains

doi:10.1088/1674-1056/adde34

Abstract Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems. The paper addresses an adaptive polynomial approximation algorithm for the cooperative control of high-speed trains (HSTs) under virtual coupling. It aims to solve the cooperative tracking control problem of HST formation operations under various scenarios, including known and unknown parameters. To enable the HST formation system to achieve cooperative operation while ensuring an appropriate spacing distance, the tracking errors of displacement and speed throughout the entire operation converge to zero. The proposed control strategy focuses on adopting polynomial approximation to handle unknown parameters, which are estimated via adaptive laws. Additionally, the unknown parameters of the HSTs are estimated online through adaptive laws. Experimental results verify the effectiveness of this method.

Keywords: high-speed trains (HSTs) cooperative operation adaptive polynomial approximation virtual coupling

Received: 07 February 2025
Revised: 20 April 2025
Accepted manuscript online: 29 May 2025

PACS:	89.40.-a	(Transportation)
	07.05.Dz	(Control systems)
	02.30.Yy	(Control theory)

Fund: This work is supported in part by the National Natural Science Foundation of China (Grant Nos. 62203246 and 62003127), Shandong Provincial Natural Science Foundation (Grant No. ZR2024QF041), and the Natural Science Foundation of Hebei Province (Grant No. F2023202060).

Corresponding Authors: Xue Lin
E-mail: xlin@qust.edu.cn

Cite this article:

Kai-Xiang Wang(王凯祥), Ming-Yue Ren(任明月), Qian-Ling Wang(王千龄), and Xue Lin(林雪) Adaptive polynomial approximation-based virtual coupled cooperative control for high-speed trains 2025 Chin. Phys. B 34 108901

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Adaptive polynomial approximation-based virtual coupled cooperative control for high-speed trains

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