基于模糊MPC的无人矿卡横向控制

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中图分类号：U461.6 文献标识码：A DOI：10.3969/j.issn.1674-8484.2025.04.010

Abstract：To addressthe issue of steering lag and improve theaccuracy of lateral control in unmanned mining trucks，this study proposed a lateral control algorithm based on fuzzy model predictive control （FMPC）.First， thevehicle dynamics modeland tracking eror model wereestablished.Subsequently，avehiclestate prediction method basedondynamic preview time wasdesigned，and the tracking eror was calculatedaccording to the predictedvehiclestateafter thepreview period.Furthermore，by integrating fuzzy control with model predictive control （MPC），an MPC controlerwas developed thatadaptivelyadjusts the weight matrices ofboth lateral error and heading angle eror.Theeffctiveness of the proposed FMPCalgorithm was validated through hardwarein-the-loopsimulationexperimentsandreal-vehicle tests.Theresults indicate that，in the hardware-in-theloopsimulation，themaximum lateral error of the FMPC algorithm isreduced by 43.0% compared to the Pure Pursuit algorithm.Inreal-vehicleexperiments conducted undertwo operational conditions—empty-load uphil drivingand heavy-load parking-themaximum lateral errorsare reducedby 50.1% and 17.6% ，respectively，in comparisontothePurePursuitalgorithm，demonstrating thatthe FMPCalgorithmachieves superiorcontrol performance and significantly enhances the lateral control accuracy of unmanned mining trucks.

Keywords：unmanned mining trucks;lateral control; steering lag;dynamic preview;fuzzy model predictive control （FMPC）

近年来，由于矿山环境恶劣，招工成本高且用工困难[，无人驾驶技术被引入矿山，以打造智慧化、无人化的生产模式。（剩余12988字）