Liu Yingjie, Cui Dawei, Peng Wen
School of Machinery and Automation, Weifang University, Weifang 261061, China.
State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819, China.
Sensors (Basel). 2023 Jul 25;23(15):6673. doi: 10.3390/s23156673.
Accurate tracking of a given path is one of the primary factors in the maneuverability of a vehicle and is also an important topic in autonomous vehicle research. To solve the problem of vehicle path tracking, the problem must first be transformed into an optimal control problem. Then, a symplectic pseudospectral method (SPM) based on the third-generation function of symplectic theory and pseudospectral discretization is proposed to efficiently solve the nonlinear optimal control problems. Finally, the results obtained by the proposed algorithm are compared with those obtained by the Gauss pseudospectral method (GPM). The simulation results show that the proposed method can effectively solve the vehicle path tracking problem. Furthermore, the vehicle can track the given path controlled by the proposed algorithm with higher accuracy and greater applicability than other methods.
精确跟踪给定路径是车辆机动性的主要因素之一，也是自动驾驶车辆研究中的一个重要课题。为了解决车辆路径跟踪问题，必须首先将该问题转化为最优控制问题。然后，提出了一种基于辛理论第三代函数和伪谱离散化的辛伪谱方法（SPM），以有效地解决非线性最优控制问题。最后，将所提算法得到的结果与高斯伪谱方法（GPM）得到的结果进行比较。仿真结果表明，所提方法能够有效地解决车辆路径跟踪问题。此外，与其他方法相比，车辆能够以更高的精度和更强的适用性跟踪由所提算法控制的给定路径。
