自主车辆线性时变模型预测路径跟踪控制

Path Tracking Using Linear Timevarying Model Predictive Control for Autonomous Vehicle

摘要:

为提高自主车辆路径跟踪控制的实时性和鲁棒性，研究一种线性时变模型预测路径跟踪控制方法.建立用于控制器仿真验证的纵向&侧向二维车辆非线性动力学模型；从二轮三自由度模型出发，推导出线性时变路径跟踪预测模型；引入向量松弛因子解决优化求解过程中硬约束导致的控制算法非可行解问题，基于模型预测控制理论将路径跟踪控制算法转化为带软约束的在线二次规划问题；最后通过Matlab/Simulink实现车辆动力学建模和控制器设计，双移线工况仿真结果表明，所设计的控制器能够适应不同车速、不同设计参数的鲁棒性要求.

Abstract:

In order to improve realtime robustness of autonomous vehicle, a path tracking approach based on linear timevarying model predictive control is investigated. The longitudinal and lateral vehicle nonlinear dynamics model is established for verification of controller simulation. Starting from twowheeled model with 3 degrees of freedom (DOFs), linear timevarying path tracking predictive model is deduced. Vector relaxation factors are introduced to deal with the nonfeasible solution caused by the hard constraints in the optimization process. Based on model predictive control theory, the design of path tracking algorithm can be transformed into an online quadratic programming problem with soft constraints. Finally, both vehicle modeling and controller design are realized based on the Matlab/Simulink software, simulation results of double lane change show that the controller can adapt to robustness of different speeds and design parameters.