针对铰接农用车在变附着系数路面条件下的路径跟踪精度难以保证的问题,提出了引入侧滑补偿的非线性模型预测控制(Nonlinear Model Predictive Control,NMPC)算法.首先,构建了考虑侧滑补偿的铰接农用车二自由度运动学模型,并基于该模型在Simulink中构建了 NMPC控制器,最后以Adams环境中的虚拟铰接农用车为被控对象,以农业典型的地头转弯路径为参考路径,开展了变附着系数路面条件下的试验验证.结果表明,该算法的跟踪误差最大约为0.03 m,能够实现铰接农用车在变附着系数路面下的高精度路径跟踪.
Study on Path Tracking Control Algorithm for Articulated Agricultural Vehicles
Addressing the challenge of maintaining path tracking precision for articulated agricultural vehicles under varying road adhesion conditions,a Nonlinear Model Predictive Control(NMPC)algorithm with introduced slip compensation was proposed.Initially,a two-degree-of-freedom kinematic model for articulated agricultural vehicles considering slip compensation was formulated.Subsequently,an NMPC controller based on this model was developed in Simulink.Finally,using a virtual articulated agricultural vehicle in the Adams environment as the controlled object and a typical agricultural headland turning path as the reference,experimental validation was conducted under variable adhesion road conditions.The results indicated that the algorithm achieved a maximum tracking error of approximately 0.03 meters,demonstrating its capability to achieve high-precision path tracking for articulated agricultural vehicles on surfaces with varying adhesion.
Path trackingArticulated vehicleNonlinear model predictive controlSlip angle
万方数据
维普
