A Model Predictive Tracking Control Study for Speed Trajectory of Autonomous Driving Trucks
In order to prevent vehicle mass changes and road slope interfering with longitudinal speed of autonomous driving truck,this article utilizes an intelligent navigation system to obtain information including vehicle speed trajectory and road slope.Vehicle longitudinal dynamic model and Compressed Natural Gas(CNG)engine dynamic model are established,and a real-time Dynamic Programming(DP)speed trajectory tracking controller is designed based on the Model Predictive Control(MPC)framework.The simulation results under NEDC and WLTC operating conditions show that the controller can keep vehicle speed stable under conditions of truck mass change and road slope interference,and can optimize speed tracking error while reducing natural gas consumption.
万方数据
维普
