School of Mechanical and Electrical Engineering, China University of Mining and Technology
Xuzhou XCMG Heavy Vehicle Co., Ltd.

露天矿无人驾驶自卸车面临道路等级低且坡道弯道多、车辆载质量大且变化范围宽等恶劣运输工况，现有车辆运动控制策略多面向普通道路环境，无法直接将现有车辆控制策略应用于矿山自卸车。针对上述问题，提出了一种基于预瞄误差与分层反馈的露天矿无人驾驶自卸车横−纵向协同控制系统。横向控制以线性二次型调节器（LQR）为基础，运用前馈控制器降低稳态误差，采用模糊控制器实现自适应调整预瞄距离，以提高路径跟踪控制精度；纵向控制建立分层反馈式纵向速度控制器，分别采用模型预测控制和模糊PID反馈控制，并建立车辆驱动及制动逆向模型，降低自卸车载质量与道路坡度改变对纵向速度追踪的影响。仿真结果表明：① 车辆实际速度和期望速度误差在2%以内，说明自卸车在空载下坡与满载上坡2种工况下的速度跟踪效果能够满足要求。② 由于横−纵向协同控制能够针对路径曲率的不同实时调节车辆速度，在2种工况下，自卸车横−纵向协同控制器相比于单一横向控制都获得了更高的路径跟踪精度，同时也提高了自卸车的操纵稳定性。实验结果表明：① 空载下坡时的横向误差峰值为0.019 9 m，方向误差峰值为0.184 0 rad，误差增大均发生在弯道处，但误差波动范围较小，能够保证试验车对期望路径的跟踪。② 负载上坡时的横向误差峰值为0.016 8 m，方向误差峰值为0.071 4 rad，误差变化趋势与空载下坡试验相反，但误差仍在合理范围内，试验车的跟踪效果良好。③ 2个误差峰值均小于空载下坡试验，验证了不同速度对横向控制精度的影响规律。

Open-pit mine unmanned dump trucks face harsh transportation conditions, such as low-grade roads with numerous ramps and curves, as well as heavy and highly variable loads. Most existing vehicle motion control strategies are designed for conventional road environments, making them unsuitable for direct application to mine dump trucks. To address these issues, a lateral-longitudinal coordinated control system based on preview error and layered feedback was proposed for unmanned open-pit mine dump trucks. The lateral control was based on a linear quadratic regulator (LQR) and employed a feedforward controller to reduce steady-state errors, while a fuzzy controller was used to adaptively adjust the preview distance, thereby improving path tracking accuracy. The longitudinal control established a layered feedback longitudinal speed controller, which used model predictive control and fuzzy proportional-integral-differential (PID) feedback control. In addition, an inverse model for vehicle driving and braking was established to minimize the impact of load and road gradient changes on longitudinal speed tracking. Simulation results indicated that: ① The error between the actual speed and the desired speed was within 2%, demonstrating that the speed tracking performance of the dump truck could meet requirements under both empty downhill and fully loaded uphill conditions. ② Due to the lateral-longitudinal coordinated control’s ability to adjust vehicle speed in real time based on varying road curvature, the coordinated controller achieved higher path tracking accuracy compared to single lateral control in both operating conditions, while also enhancing vehicle maneuverability and stability. Laboratory test results showed that: ① The peak lateral error during empty downhill runs was 0.0199 m, and the peak direction error was 0.1840 rad. Both errors increased at curves, but their fluctuations were minimal, ensuring that the test vehicle effectively tracked the desired path. ② During loaded uphill runs, the peak lateral error was 0.0168 m, and the peak direction error was 0.0714 rad. The error trends were opposite to those observed in empty downhill tests, but the errors remained within acceptable limits, resulting in good path tracking performance. ③ Both peak errors were lower compared to those in empty downhill tests, which validated the effect of varying speeds on lateral control accuracy.

江苏省科技成果转化专项资金项目（BA2023035）；徐州市重点研发计划资助项目(KC22419)；江苏高校优势学科建设工程资助项目（PAPD）。

潘国宇，鲍久圣，胡德平，等. 露天矿无人驾驶自卸车横−纵向协同控制研究[J]. 工矿自动化，2024，50（10）：68-79.

PAN Guoyu, BAO Jiusheng, HU Deping, et al. Research on lateral-longitudinal coordinated control of unmanned dump trucks in open-pit mine[J]. Journal of Mine Automation，2024，50（10）：68-79.