矿用卡车路面自适应模型预测轨迹跟踪控制

Mine truck trajectory tracking based on road adaptive model predictive control

针对矿区道路环境突变对无人矿用卡车无人驾驶的挑战,本文研究了路面自适应模型预测轨迹跟踪控制问题.首先,根据矿区常用矿卡车型及环境突变特点分别建立矿卡动力学模型和矿区道路环境模型;其次,提出矿卡路面自适应模型预测轨迹跟踪控制框架;然后,引入预设附着系数库,提出基于自主切换策略的最小二乘参数估计方法以应对突变工况做出合理递推;最后,提出矿卡路面自适应模型预测轨迹跟踪控制方法.仿真表明,所提方法比传统自适应模型预测控制方法轨迹跟踪精度更高,可以充分考虑道路附着条件突变的矿区道路工况,自适应地保证矿卡的操纵稳定性.

In order to eliminate the influence of road parameters uncertainty in mine truck trajectory tracking,this paper proposes a road-adaptive trajectory tracking controller based on the adaptive control and model predictive control.Firstly,the dynamics model of the mining truck and the environmental model of the mining road are established respectively according to the common mining trucks’type and the of the sudden change of the environment.Secondly,the framework of mine truck trajectory tracking based on the road adaptive model predictive control is proposed.Thirdly,a least-squares parameter estimation method based on the autonomous switching strategy is proposed to make reasonable recursion for sudden-changed road conditions.Finally,a mine truck trajectory tracking based on the road adaptive model predictive control is proposed.The simulation results show that the proposed method has higher trajectory tracking accuracy than the traditional adaptive model predictive control method.The method can fully consider the road conditions in mining areas with uncertainty parameters and sudden changes,and adaptively ensures the handling stability of the mining truck.