基于模型预测的主动转向智能无人车辆横向稳态控制

In the complex road conditions and the steering process of intelligent unmanned vehicle, the vehicle is in a time-varying unstable state, causing the vehicle handling insecurity and driving instability. In this paper, an optimal model predictive control strategy was proposed for the front wheel active steering unmanned vehicle. Firstly, a hierarchical structure was designed for the controller to optimize the front wheel steering angle of the vehicle and to improve the characteristics of the vehicle body under the unsteady state. And then, taking into account the internal and external disturbance factors of the unmanned vehicle in actual driving, the nonlinear disturbance platform model and nonlinear tire model were established, and the nonlinear dynamic model of the unmanned vehicle was built through the modular method. Finally, a nonlinear disturbance observer was used to suppress the disturbance, improving the accuracy of the vehicle model and the control effect of the controller. The results of simulation and hardware-in-the-loop test show that the stability of the vehicle can be improved by 55% compared with the vehicle without lateral stability control, verifying that the control strategy can significantly improve the lateral stability and effectiveness of the vehicle.