Considering that when a vehicle travels on a low friction coefficient road with high speed, the path tracking ability declines. To keep the performance of path tracking and improve the stabilization under that situation, this article presents approaches to estimate the parameters and control the vehicle. First, the key states of the vehicle and the road adhesion coefficient are estimated by the unscented Kalman filter. This is followed by applying the linear time-varying model-based predictive controller to achieve path tracking control, and the initial tire steering angle control rate is obtained. Finally, the steering angle compensation controller is simultaneously designed by a simple receding horizon corrector algorithm to improve vehicle stability when the path is tracked on a low-adhesion coefficient or at high speed. The performance of the proposed approach is evaluated by software CarSim and MATLAB/Simulink. Simulation results show that an improvement in the performance of path tracking and stabilization can be achieved by the integrated controller under the variable road adhesion coefficient condition and high speed with 110 km/h.

考虑到当车辆在低摩擦系数的道路上高速行驶时，路径跟踪能力下降。为了在这种情况下保持路径跟踪的性能并提高稳定性，本文提出了估计参数和控制车辆的方法。首先，通过无味卡尔曼滤波器估计车辆的关键状态和道路附着系数。接下来，应用基于线性时变模型的预测控制器来实现路径跟踪控制，并获得初始轮胎转向角控制率。最后，转向角补偿控制器由一个简单的后视水平校正器算法同时设计，以在以低附着系数或高速跟踪路径时提高车辆稳定性。所提出方法的性能由软件CarSim和MATLAB / Simulink评估。仿真结果表明，在可变道路附着系数条件下，以110 km / h的高速行驶时，集成控制器可以改善路径跟踪和稳定性能。