Dual Closed-Loop Control of Intelligent Vehicles Trajectory Tracking Based on Steering Response Characteristics
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摘要: 智能车辆轨迹跟踪的准确性与鲁棒性是车辆运动控制性能的重要表征，基于路径预瞄信息的跟踪控制研究使车辆性能显著提升. 然而，车辆转向系统响应不足给车辆实时准确的基于预瞄信息跟踪参考轨迹带来挑战. 针对此问题，实时引入转向系统状态建立双闭环轨迹跟踪控制结构，保证智能车辆轨迹跟踪控制算法对转向系统响应不足的鲁棒性. 具体结构外环基于预瞄信息使用模型预测控制求解最优转向角，内环基于转向状态误差使用PID方法设计反馈控制律以补偿转向响应不足. 双闭环结构耦合控制输入保证了车辆鲁棒最优跟踪控制. 最后通过Carsim与Simulink联合仿真，验证了该双闭环控制结构的有效性.Abstract: The accuracy and robustness of intelligent vehicle trajectory tracking are important characteristic of vehicle motion control performance. Many Researches of tracking control based on path preview information have significantly improved vehicle performance. However, the insufficient response of the vehicle steering system have caused many difficulties for the vehicle to accurately track the reference trajectory based on the preview information in real time. To solve this problem, introducing state of the steering system in real time, a dual closed-loop trajectory tracking control structure was established to ensure the robustness of the intelligent vehicle trajectory tracking control algorithm for the insufficient response of the steering system. Concretely, in the outer loop of this structure, a model predictive control method was used to solve the optimal steering angle based on preview information. And in the inner loop of this structure, a PID method was used to design a feedback control law based on steering state error to compensate for insufficient steering response. Coupling control input, the dual closed-loop structure can ensure the robust optimal tracking control of the vehicle. Finally, the effectiveness of the dual closed-loop control structure was verified in Carsim and Simulink co-simulation.
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表 1 传统MPC＆双闭环控制误差
Table 1. Traditional MPC & dual closed loop control rms value
算法 横向误差/m 前轮转角误差
/(°)传统MPC 0.826 0.212 双闭环控制 0.221 0.118 
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表 2 横向误差均方根值对比
Table 2. Comparison of RMS Value of Lateral Error
转向响应特性 MPC 双闭环 0.9 0.627 0.097 0.925 0.545 0.081 0.95 0.453 0.083 0.975 0.364 0.060 1 0.273 0.062
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