改进的LQR横向路径跟踪控制器
An Improved Lateral Path Tracking Controller Based on Linear Quadratic Regulator
马思群 1王兆强 1韩博 1赵佳伟1
作者信息
- 1. 上海工程技术大学 机械与汽车工程学院,上海 201620
- 折叠
摘要
路径跟踪在自动驾驶中起着至关重要的作用.为了保证控制器的实时性并提高路径跟踪控制器的稳定性和自适应性,提出了一种基于改进的LQR算法的横向路径控制策略.首先将汽车的动力学模型拆解为横向误差动力学模型,并以此模型设计了前馈+反馈的离散LQR控制器.然后采用模糊控制方法实时根据车辆状态调整LQR的权重系数.此外,为了降低控制器的计算量,设计了基于余弦相似度的更新机制.最后,通过Simulink-Carsim平台对改进的LQR控制器进行双移线路况测试.结果表明,该控制算法在跟踪精度和计算效率方面得到了较大的改善.
Abstract
Path tracking plays an indispensable role in the autonomous driving of a vehicle.In order to ensure the real-time performance of the path tracking controller and improve its stability and adaptability,we improved a lateral path tracking controller based on the linear quadratic regulator(LQR).Firstly,we transform the vehicle's dynamics model into a lateral error dynamics model.Based on this model,a feedforward plus feedback discrete LQR controller is designed.Then,the fuzzy control method is used to adjust the weighted coefficient of the LQR in real time according to the vehicle's state.In addition,an update mechanism based on the cosine similarity is designed to reduce the calculation volume of the controller.Finally,the improved lateral path tracking controller was tested on the double change lane path through the Simulink-Carsim platform.The test results show that the controller dramatically improves the tracking accuracy,steering stability,and calculation efficiency.
关键词
路径跟踪/线性二次型调节器(LQR)/拉格朗日乘数法/权重自适应控制/余弦相似度Key words
path tracking/linear quadratic regulator/Lagrange multiplier/weighted adaptive control/cosine similarity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