基于LQR的智能驾驶汽车横纵向控制研究
Research on Hovizontal and Longitudinal Control of Intelligent Driving Vehicle based on LQR
高爱云 1肖寒 1付主木2
作者信息
- 1. 河南科技大学车辆与交通工程学院,河南 洛阳 471023
- 2. 河南科技大学信息工程学院,河南 洛阳 471023
- 折叠
摘要
为了提高智能驾驶汽车跟踪控制器的稳定性和跟踪精度,提出了一种基于线性二次型调节器(LQR)控制算法和驾驶员预瞄模型的横向跟踪控制策略,结合纵向比例-积分-微分(PID)控制算法实现横纵向控制.首先建立带有前馈的 LQR控制器,采用梯度下降优化算法优化 LQR 控制器权重参数,并在此基础上引入驾驶员预瞄模型,设计了基于经验的预瞄距离自适应控制器;其次建立双 PID 纵向控制器进行速度控制.最后通过 Carsim和 Matlab/Simulink联合仿真以及实车测试验证,结果表明:仿真工况下最大横向偏差小于 0.035 m,最大航向偏差小于 0.09 rad,实车测试工况下也能够良好遵循规划轨迹的整体趋势,速度跟踪效果良好且前轮转角与横摆角速度变化平稳.因此,该控制器能够保证较高精度且平稳的轨迹跟踪,在高速状态下更为明显.
Abstract
To improve the stability and tracking accuracy of intelligent driving vehicle tracking controller,a lateral tracking control strategy based on LQR control algorithm and driver preview model is proposed,and combined with the longitudinal PID control algorithm to achieve lateral and longitudinal control.Firstly,a LQR controller with feed-forward is established,and the weight parameters of the LQR controller are optimized by gradient descent optimization algorithm.On this basis,the preview model of the driver is introduced,and an adaptive controller for preview distance based on experience is designed.Secondly,dual PID longitudinal controllers are established for velocity control.Finally,the test verification is carried out through Carsim and Matlab/Simulink joint simulation and real vehicle.The results show that the maximum lateral deviation of simulation is less than 0.035 m,the maximum heading deviation is less than 0.09 rad,the overall trend of the planned trajectory can also be well followed under real vehicle test conditions,and the front wheel rotation angle and yaw rate change smoothly.The controller can ensure high-precision and smooth trajectory tracking,and it is more obvious at high velocity.
关键词
智能驾驶汽车/轨迹跟踪/线性二次型/梯度下降法/驾驶员模型Key words
intelligent driving vehicle/trajectory tracking/LQR/gradient descent/driver model引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据