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

智能车路径跟踪控制受到车辆参数摄动、场景多变等干扰,影响路径跟踪精确性,甚至引起控制系统不稳定.本文设计了考虑不确定性的二阶超螺旋滑模鲁棒控制算法,证明了控制系统的收敛性,并针对干扰问题设计了前馈补偿控制器以进一步提升控制系统的精确性.通过Carsim-Simulink联合仿真环境下的双移线、正弦路径跟踪控制,以及参数摄动情况下的路径跟踪控制,与传统一阶滑模控制对比,验证了所设计的超螺旋滑模控制器路径跟踪的精确性及鲁棒性.结果表明,面对智能车辆参数不确定、驾驶场景多变等情况,采用超螺旋滑模算法比传统滑模算法具有更好的鲁棒性和跟踪精度,超螺旋算法能有效地减弱传统滑模算法产生的方向盘抖振问题.最后,利用实车平台对进行了低速大曲率场景测试,验证所设计的超螺旋滑模算法控制器具有良好的路径跟踪精度.

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.