南京信息工程大学学报2025，Vol.17Issue(3)：352-362,11.DOI:10.13878/j.cnki.jnuist.20240428001
基于WOA-LQR的智能车辆路径跟踪控制
Intelligent vehicle path tracking control via WOA-LQR
摘要
Abstract
Here,a Linear Quadratic Regulator(LQR),optimized using the Whale Optimization Algorithm(WOA)and hence referred to as the WOA-LQR controller,is designed to address the issue of poor path-tracking control ac-curacy for autonomous vehicles under special driving conditions(such as icy and snowy roads,rainy surfaces,and high-speed lane changes).Initially,a tracking error model is established based on a two-degree-of-freedom vehicle dynamics model,and a discrete LQR controller is designed on this basis.Feedforward control is employed to elimi-nate errors caused by system simplification.To address the problem of low tracking accuracy and vehicle instability under special driving conditions due to the poor adaptability of the LQR controller with fixed weight coefficients,an adaptive weight adjustment strategy for the LQR controller is proposed based on WOA.This strategy takes into ac-count the influence of lateral acceleration and front wheel steering angle on vehicle stability and assigns correspond-ing weight coefficients to the evaluation indices,which include lateral error and yaw angle error.A fitness function with the minimum target value is designed to optimize the LQR weight coefficients using WOA.Finally,the WOA-LQR controller is tested and validated through path-tracking simulations under various conditions using Carsim/Sim-ulink co-simulation.The results demonstrate that the proposed control strategy provides excellent tracking perform-ance under complex driving conditions,significantly improves the control accuracy during path tracking,and exhibits strong robustness.关键词
无人驾驶车辆/路径跟踪控制/线性二次型调节器/前馈控制/鲸鱼优化算法Key words
autonomous vehicles/path tracking control/linear quadratic regulator(LQR)/feedforward control/whale optimization algorithm(WOA)分类
交通运输引用本文复制引用
张闯,赵奉奎,张涌,张伟..基于WOA-LQR的智能车辆路径跟踪控制[J].南京信息工程大学学报,2025,17(3):352-362,11.基金项目
江苏省重点研发计划(产业前瞻与关键核心技术)(BE2022053-2) （产业前瞻与关键核心技术）
江苏省重点研发计划(现代农业)(BE2021339) （现代农业）
南京林业大学青年科技创新基金(CX2019018) （CX2019018）
江苏省特种设备安全监督检验研究院吴江院项目(KI(Y)2023042) （KI(Y）
