摘要
近年来研究者们发现前轮转角速度约束等系统约束对路径跟踪控制的性能存在较大的影响,而常用于解决系统约束影响的模型预测控制存在实时性较差的问题。为此基于计算成本较低的Stanley控制,考虑前轮转角速度约束等系统约束的影响,提出了一种考虑系统约束的预瞄Stanley车辆(无人驾驶)路径跟踪控制算法,并通过MATLAB与Carsim联合仿真对该算法进行了仿真测试。在被控对象有系统约束的情况下,提出的控制方法仍具有较高的精确性和实时性,其中横向误差绝对值不超过0.2734 m,航向误差绝对值不超过0.1135 rad,每个控制周期内的计算时间不超过2 ms。仿真结果还表明,该控制方法在精确性方面优于经典Stanley控制、已有的未考虑系统约束的预瞄Stanley控制,在实时性方面优于模型预测控制。
In recent years,researchers have found that system constraints such as front wheel angle speed constraints greatly impact the performance of path tracking control.However,model predictive control,commonly used to deal with the influence of system constraints,has the problem of poor real-time performance.To this end,based on Stanley control with low computation cost,an unmanned vehicle path tracking control method based on preview Stanley control was proposed considering the influence of system constraints such as front wheel angle speed constraints.This control method uses the nearest point on the reference path to the midpoint of the front axle to calculate the displacement control law,and uses the preview point ahead of the vehicle to calculate the heading control law,thus enabling the controller to reduce the effect of system constraints by responding in advance.The proposed control method is tested by joint simulation of MATLAB and Carsim.In the case that the controlled object has system constraints,the proposed control method still has high accuracy and real-time performance,in which the absolute value of displacement error does not exceed 0.2743 m,the absolute value of heading error does not exceed 0.1135 rad,and the calculation time in each control cycle does not exceed 2 ms.The simulation results also show that the control method outperforms classical Stanley control and existing preview Stanley control without considering system constraints in terms of accuracy and outperforms model predictive control in terms of real-time.
作者
张俊娜
白国星
ZHANG Junna;BAI Guoxing(Department of Automotive Engineering,Shanxi Institute of Mechanical and Electrical Engineering,Changzhi 046011,China;School of Mechanical Engineering,Beijing University of Science and Technology,Beijing 100083,China)
出处
《现代制造工程》
CSCD
北大核心
2023年第9期61-68,共8页
Modern Manufacturing Engineering
基金
国家重点研发计划资助项目(2018YFE0192900)
中国博士后科学基金资助项目(2022M710354)
中央高校基本科研业务费专项资金资助项目(FRF-TP-20-052A1)。
作者简介
张俊娜,讲师,硕士,长期从事智能无人车领域的研究、教学工作;白国星,讲师,博士,长期从事无人驾驶车辆、移动机器人领域的研究工作,主要研究兴趣包括路径跟踪控制、模型预测控制等。E-mail:gxbai@ustb.edu.cn。
