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Article
Publication date: 10 February 2023

Junting Lin, Mingjun Ni and Huadian Liang

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under…

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Abstract

Purpose

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.

Design/methodology/approach

The mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.

Findings

The simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity.

Originality/value

The algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.

Details

Railway Sciences, vol. 2 no. 1
Type: Research Article
ISSN: 2755-0907

Keywords

Available. Open Access. Open Access

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

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Only Open Access

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