考虑横摆稳定性的无人车轨迹跟踪控制优化研究

Vehicle yaw stability and the performance of path-following are crucial to autonomous vehicles. A path-following controller based on model predictive control is designed. The stability criterion considering the instantaneous limit performance is added to the controller constraints, and the controller parameters are optimized in a performance-driven manner. Firstly, we established the phase plane of the yaw rate and the sideslip angle according to the vehicle's three-degree-of-freedom dynamic model, and the influence of the steering angle on the phase plane balance point is analyzed. By establishing the isotropic geometry of the phase plane, the stability characteristics of the vehicle are analyzed and the yaw stability criterion based on the envelope is formed. Secondly, we parameterize the cost function of the model predictive controller and design the global cost function of a specific scenario as the performance evaluation function, we use Bayesian optimization to optimize the prediction horizon and cost function weights to achieve the optimal global performance under target task. Finally, the simulation and real vehicle test show the algorithm exerts the vehicle to the dynamic limits and improves the tracking performance.