湖南大学学报（自然科学版）2024，Vol.51Issue(2)：151-162,12.DOI:10.16339/j.cnki.hdxbzkb.2024154
基于超螺旋滑模及前馈补偿的智能车侧向运动控制
Lateral Motion Control of Intelligent Vehicle Based on Combination of Super-twisting Sliding Mode and Feedforward Compensation Algorithms
摘要
Abstract
Intelligent vehicle path tracking control is faced with interferences such as vehicle parameter perturbation and scene variability,which affects the accuracy of path tracking,and even causes the control system instability.In this paper,a second-order super-twisting sliding mode robust control algorithm considering uncertainty is designed,the convergence of control system is proved,and a feedforward compensation controller is designed for interference problems to further improve the accuracy of the control system.Then,to validate the accuracy and robustness of the proposed robust control algorithm,several cases including double-lane change,sine path,as well as parameter perturbation scenes,are simulated under the Carsim-Matlab/Simulink co-simulation environment,and the traditional first-order sliding mode control is selected as a comparison.The results show that,the proposed super-twisting sliding mode algorithm has better robustness and tracking accuracy than the traditional sliding mode algorithm when considering the above interferences.Meanwhile,the proposed super-twisting algorithm can effectively reduce the steering wheel buffeting problem which exists in the traditional sliding mode algorithm.Finally,the large curvature scene travelling at low speed is tested on the real vehicle platform to verify the more accurate path-tracking effect of the designed super-twisting sliding mode algorithm.关键词
智能车/路径跟踪/鲁棒性/超螺旋滑模算法/前馈补偿Key words
intelligent vehicle/path tracking/robustness/super-twisting sliding mode algorithm/feedforward compensation分类
交通工程引用本文复制引用
吴晓建,张明华,王爱春,关龙新,江会华,彭晨若..基于超螺旋滑模及前馈补偿的智能车侧向运动控制[J].湖南大学学报（自然科学版）,2024,51(2):151-162,12.基金项目
国家自然科学基金资助项目(52262054,52002163,52062036),National Natural Science Foundation of China(52262054,52002163,52062036) （52262054,52002163,52062036）
