Title: Investigation of MPC path tracking control for articulated unmanned mining trucks in reversing environments of mining areas

Authors: Qing Ye; Kongjia Meng; Ruocheng Wang; Zeyu Sun; Yao Zhang

Addresses: Automotive Engineering Research Institute, Jiangsu University, No. 301, Xuefu Road, Jingkou District, Zhenjiang, 212013, Jiangsu, China ' Automotive Engineering Research Institute, Jiangsu University, No. 301, Xuefu Road, Jingkou District, Zhenjiang, 212013, Jiangsu, China ' Automotive Engineering Research Institute, Jiangsu University, No. 301, Xuefu Road, Jingkou District, Zhenjiang, 212013, Jiangsu, China ' School of Agricultural Engineering, Jiangsu University, No. 301, Xuefu Road, Jingkou District, Zhenjiang, 212013, Jiangsu, China ' School of Electrical and Information Engineering, Jiangsu University, No. 301, Xuefu Road, Jingkou District, Zhenjiang, 212013, Jiangsu, China

Abstract: This paper introduces a trajectory tracking control algorithm for articulated autonomous mining trucks during reversing, utilising model predictive control (MPC) to address vehicle articulation challenges. A dynamic model with three degrees of freedom is established to analyse the reverse motion characteristics of these trucks, which forms the basis for developing a virtual steering angle mapping model tailored for reversing manoeuvres. Subsequently, an MPC path tracking algorithm is proposed, emphasising lateral stabilisation control torque for both the tractor and the semi-trailer to ensure precise tracking control of the articulated system. Hardware-in-the-loop (HIL) testing, along with simulation and experimental results, demonstrates that the proposed control strategy effectively satisfies reversing control requirements. It also outperforms conventional preview control and PID control methods, further validating the efficacy of the algorithm.

Keywords: MPC; model predictive control; unmanned mining trucks; reverse movement; HIL; hardware-in-the-loop.

DOI: 10.1504/IJHVS.2025.150203

International Journal of Heavy Vehicle Systems, 2025 Vol.32 No.6, pp.711 - 733

Received: 12 Jun 2024
Accepted: 02 Dec 2024
Published online: 03 Dec 2025 *

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