基于自抗扰控制的自动驾驶车辆轨迹跟踪研究

Research on Self-Driving Vehicle Trajectory Tracking Based on Self-Immunity Control

摘要: 针对道路曲率和不同车速工况下自动驾驶车辆运动控制过程中轨迹跟踪精度和稳定性难以同时保障的问题，设计一种自抗扰控制(ADRC)算法，通过控制横向误差来获得前轮转角，以保证车辆的跟踪精度和稳定性，并基于粒子群优化算法同时整定传统比例–积分–微分(PID)和ADRC的关键参数，从而进一步说明所设计算法的控制效果。该控制算法具有对模型精度要求低、适应性强、以及能够估计和补偿未知扰动的优点。在Matlab/CarSim联合仿真平台上，同在双移线工况中的不同车速下对该算法和PID算法进行了仿真验证和比较。此外，为了进一步验证所提算法的优势，在实车实验中也对这两种算法进行了对比分析。仿真实车结果表明，所提出的ADRC控制算法具有更强的鲁棒性，能够有效改善由于道路曲率变化和不同车速下引起的车辆抖动问题，实现更加精确、稳定的轨迹跟踪效果。

Abstract: Aiming at the problem that it is difficult to guarantee the trajectory tracking accuracy and stability at the same time during the motion control process of self-driving vehicles under the road curvature and different speed conditions, a kind of auto-resistant control (ADRC) algorithm is designed to obtain the front-wheel turning angle by controlling the transverse error in order to guarantee the tracking accuracy and stability of the vehicle and the key parameters of the traditional proportional-integral-derivative (PID) and ADRC are rectified at the same time based on the particle swarm optimization algorithm, so as to further illustrate the control effect of the designed algorithm. The key parameters of traditional proportional-integral-derivative (PID) and ADRC are simultaneously adjusted based on the particle swarm optimization algorithm to further illustrate the control effect of the designed algorithm. The control algorithm has the advantages of low model accuracy requirements, high adaptability, as well as the ability to estimate and compensate for unknown disturbances. The algorithm is validated and compared with the PID algorithm on the Matlab/CarSim joint simulation platform at different vehicle speeds in the same double-shifted line condition. In addition, in order to further verify the advantages of the proposed algorithm, the two algorithms are also compared and analyzed in real vehicle experiments. The simulated real-vehicle results show that the proposed ADRC control algorithm has stronger robustness and can effectively improve the vehicle jitter problem caused by the change of road curvature and different speeds, and realize more accurate and stable trajectory tracking effect.