Formation control of unmanned dump truck in narrow curved section of open-pit mine based on LQR and DMPC method

The core risks of unmanned truck formations in narrow curved sections of open-pit mines mainly include lateral trajectory deviation risk and longitudinal following coordination risk, which can lead to inaccurate heading angle and improper following control. Therefore, a multi-vehicle formation collaborative control method based on LQR and DMPC is proposed. The research objective is to design a collaborative control strategy that is suitable for narrow curved sections of open-pit mines, achieving precise lateral trajectory tracking and safe longitudinal following. Firstly, a multi-vehicle collaborative control scheme is designed by analyzing the transportation conditions. Secondly, the lateral dynamics model and the preview error model are established. Besides, the lateral controller based on feedforward LQR is designed. Then, based on the longitudinal dynamic characteristics of the vehicle, the multi-vehicle formation longitudinal controller based on DMPC is designed. Next, the multi-vehicle formation collaborative controller is established. Finally, the Simulink/TruckSim joint simulation model is constructed, and the unmanned experimental vehicle and open-pit mining experimental platform are designed for conducting simulations and experiments. The simulation results show that collaborative control reduces the lateral error of the following vehicle by 37.20% and the heading angle error by 36.40% when driving downhill with no load. Furthermore, collaborative control reduces the lateral error of the following vehicle by 21.95% and the heading angle error by 39.54% when fully loaded uphill. At the same time, the longitudinal following vehicle maintains a speed error of no more than 0.35 km/h and a spacing error of less than 0.30 m compared to the leading vehicle. The experimental results show that the designed formation controller controls the lateral error of the following vehicle within ±0.035 m and the heading angle error does not exceed 0.15 rad, verifying the effectiveness and adaptability of the studied formation control method.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2026-02-21
DOI
https://doi.org/10.1177/09544062261419546
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Formation control of unmanned dump truck in narrow curved section of open-pit mine based on LQR and DMPC method

Yin Yan, Zhang Kekun, Bao Jiusheng, Zhu Chenzhong et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Distributed Control Multi-Agent Systems
article

Formation control of unmanned dump truck in narrow curved section of open-pit mine based on LQR and DMPC method

Yin Yan, Zhang Kekun, Bao Jiusheng, Zhu Chenzhong, Xu Shiwei, Hu Deping, Sun Yuxiang, Wang Maosen
article en

Abstract

The core risks of unmanned truck formations in narrow curved sections of open-pit mines mainly include lateral trajectory deviation risk and longitudinal following coordination risk, which can lead to inaccurate heading angle and improper following control. Therefore, a multi-vehicle formation collaborative control method based on LQR and DMPC is proposed. The research objective is to design a collaborative control strategy that is suitable for narrow curved sections of open-pit mines, achieving precise lateral trajectory tracking and safe longitudinal following. Firstly, a multi-vehicle collaborative control scheme is designed by analyzing the transportation conditions. Secondly, the lateral dynamics model and the preview error model are established. Besides, the lateral controller based on feedforward LQR is designed. Then, based on the longitudinal dynamic characteristics of the vehicle, the multi-vehicle formation longitudinal controller based on DMPC is designed. Next, the multi-vehicle formation collaborative controller is established. Finally, the Simulink/TruckSim joint simulation model is constructed, and the unmanned experimental vehicle and open-pit mining experimental platform are designed for conducting simulations and experiments. The simulation results show that collaborative control reduces the lateral error of the following vehicle by 37.20% and the heading angle error by 36.40% when driving downhill with no load. Furthermore, collaborative control reduces the lateral error of the following vehicle by 21.95% and the heading angle error by 39.54% when fully loaded uphill. At the same time, the longitudinal following vehicle maintains a speed error of no more than 0.35 km/h and a spacing error of less than 0.30 m compared to the leading vehicle. The experimental results show that the designed formation controller controls the lateral error of the following vehicle within ±0.035 m and the heading angle error does not exceed 0.15 rad, verifying the effectiveness and adaptability of the studied formation control method.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
City University of Hong Kong (HK), China University of Mining and Technology (CN), Xuzhou Construction Machinery Group (China) (CN)
Openalex Percentile: Top 55%
Distributed Control Multi-Agent Systems
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