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滑移转向无人车轨迹跟踪控制策略研究

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针对滑移转向车辆构型的无人车,通过建立车辆动力学和运动学模型,对LQR(linear quadratic regulator)最优控制算法进行改进,在速度环采用一种自抗滑移的前馈控制,设计了一种轨迹跟踪控制策略.前馈控制有效提高了横摆角速度响应速度,可进一步优化LQR估计器的参数矩阵,保证车辆在提高轨迹跟踪控制精度的同时不影响跟随稳定性.采用Trucksim与Simulink联合仿真进行验证,结果表明:在双移线测试工况下,使用该控制策略的无人车最大横向误差比在双PID控制下小0.086 m,误差收敛速度2.1 s,稳态误差振荡幅值比滑模控制小约0.05 m;不同车速和不同附着系数路面下,无人车最大横向误差浮动小于0.02 m,误差收敛速度不变,设计算法控制效果稳定,验证了其鲁棒性.
Research on trajectory tracking control strategy of slip-steering unmanned vehicle
A trajectory tracking control strategy is designed for the unmanned vehicle with slip-steering vehicle configuration.The vehicle dynamics and kinematics models were established,the LQR(Linear Quadratic Regulator)optimal control algorithm was improved,and the feed forward control with auto-skid resistance was used to supplement the speed loop.The feed forward control was designed to improve the yaw velocity response speed and optimize the parameter matrix of the LQR estimator,which ensured that the vehicle trajectory tracking control accuracy was improved while the following stability was not affected.Trucksim and Simulink co-simulation were used to verify the results.The results show that the maximum lateral error of the unmanned vehicle using the proposed control strategy is 0.086 m smaller than that under the dual-PID control,and the error convergence rate is about 2.1 s faster.The steady-state error amplitude is about 0.05 m smaller than that of sliding mode control.Under different road speeds and adhesion coefficients,the maximum lateral error floating of unmanned vehicle is less than 0.02 m,and the error convergence speed remains unchanged.The control effect of the proposed algorithm is stable and its robustness is verified.

slip-steeringtrajectory tracking controlLQR optimal control algorithmfeed forward controloptimal control

娄岱松、朱纪洪、杨嘉睿、许志伟、毛汉领

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广西大学机械工程学院,南宁 530004

清华大学精密仪器系,北京 100084

滑移转向 轨迹跟踪 LQR算法 前馈控制 最优控制

国家自然科学基金广西科技基地和人才专项项目

51365006AD19259002

2024

兵器装备工程学报
重庆市(四川省)兵工学会 重庆理工大学

兵器装备工程学报

CSTPCD北大核心
影响因子:0.478
ISSN:2096-2304
年,卷(期):2024.45(1)
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