基于双率采样的智能车辆弯道轨迹跟踪控制

本文研究在双率采样下智能车辆弯道轨迹跟踪问题.首先,针对车辆车道保持的转向控制,建立相对路面误差的侧向动力学模型.其次,假设系统状态变量被分为两个子向量并分别由两类传感器以不同的采样周期采样,针对这类双率采样系统,充分考虑这两类传感器的采样时刻特征,设计一类基于采样时刻的切换控制器.然后,利用输入时滞方法,将最终的闭环系统建模为带有两个模态的切换时滞系统,并以线性矩阵不等式(LMI)形式给出闭环系统指数稳定性条件和切换控制器的设计方法.最后,在Matlab/Simulink环境下对汽车模型的路径跟踪控制进行仿真,验证本文所提方法的有效性,并与单率采样方法进行比较,说明本文方法相比于单率采样方法的优势.

Trajectory tracking control of intelligent vehicle on curve lane via dual rate sampling

A control method for trajectory tracking of intelligent vehicles was proposed by employing dual rate sampling. Firstly, the vehicle lateral dynamics model with relative error to the road was established for lane keeping steering control. Secondly, taking into account different sampling periods of various sensors, the state variables of the linear system were classified into two categories and each category was paired with a different sampling period. For this kind of dual rate sampling system, a periodically switched controller was proposed based on whether the sampling information about these two categories of state variables was available. Then,using the input delay approach, the resulting dual rate control system was modeled as a switched system with two timevarying sawtooth delays. The exponential stability condition of this closed loop system and the design procedure of the switching controller were established in terms of linear matrix inequalities (LMI). Finally, the trajectory tracking control was simulated by Matlab/Simulink. It was shown that the dual rate sampling method can achieve a better control performance compared with the existing single rate sampling method, which illustrates the rationality and effectiveness of the proposed method.