The current path tracking control method is usually based on the steering wheel angle loop, which often makes the driver lose control of the automatic driving control loop. In order to involve the driver in the automatic driving control loop, and to solve the vehicle path tracking control problem with system robustness and model uncertainty, this paper puts forward a steering torque control method based on model predictive control algorithm. Based on the vehicle model, this method introduces the steering system model and the steering resistance torque model, and calculates the optimal control torque of the vehicle through the real-time vehicle status, so as to make up for the model mismatch, interference and other uncertainties, and ensure the real-time participation of the driver in the automatic driving control loop. To combine the nonlinear vehicle dynamics model with the steering column model, and to take the vehicle state parameters as the feedback variables of the model predictive controller model, then input the solution of the steering superposition control rate into the vehicle model, the design of the steering controller is realized. Finally, to carry out the simulation of lane keeping based on CarSim software and Simulink control model, and the hardware in-the-loop test on the hardware in-the-loop experimental platform of CarSim/LabVIEW-RT. The simulation and test results indicate that the designed torque loop path tracking control method based on model predictive control can help the driver track the target path better.

目前的路径跟踪控制方法通常基于方向盘角度环，这常常使驾驶员失去对自动驾驶控制环的控制。为了让驾驶员参与到自动驾驶控制环中，同时解决具有系统鲁棒性和模型不确定性的车辆路径跟踪控制问题，提出一种基于模型预测控制算法的转向扭矩控制方法。该方法在车辆模型的基础上，引入转向系统模型和转向阻力矩模型，通过实时车辆状态计算出车辆的最优控制扭矩，从而弥补模型失配、干扰等问题。不确定性，并保证驾驶员实时参与自动驾驶控制回路。将非线性车辆动力学模型与转向柱模型相结合，以车辆状态参数作为模型预测控制器模型的反馈变量，将转向叠加控制率的解输入到车辆模型中，设计了实现了转向控制器。最后，基于CarSim软件和Simulink控制模型进行车道保持仿真，并在CarSim/LabVIEW-RT硬件在环实验平台上进行硬件在环测试。仿真和测试结果表明，所设计的基于模型预测控制的扭矩环路径跟踪控制方法能够帮助驾驶员更好地跟踪目标路径。