Abstract:The scraper is an articulated vehicle with the functions of shoveling and transporting soil. This kind of vehicle is often used for underground ore transportation. Path tracking control is one of the core technologies to realize the automatic driving of this kind of equipment. Aiming at the problems of large inertia, slow response, many constraints and easy snake swing, a model predictive control algorithm for articulated vehicle path tracking is proposed in this paper. In this paper, the kinematic model is used to predict future vehicle driving status. The objective function is to minimize the lateral deviation, longitudinal deviation, heading angle deviation, and articulation angle deviation of path tracking. The optimal control parameters of vehicle speed and corner speed are solved according to the steering, acceleration and deceleration, and vehicle speed constraints of the actual vehicle. Matlab/Maplesim software is used for simulation tests. The results show that the controller can achieve the control accuracy of Y-direction deviation within 0.06 m, heading angle deviation within 0.3°, and the maximum articulation angle control deviation less than 0.8°. The real vehicle test is carried out in the -645 middle section of the Sanshandao gold mine to realize the automatic driving from the main roadway to the working area. The algorithm has practical industrial application prospects and reference value.