A Nonlinear Model Predictive Control (NMPC) strategy aimed at controlling a small-scale car model for autonomous racing competitions is presented in this paper. The proposed control strategy is concerned with minimizing the lap time while keeping the vehicle within track boundaries. The optimization problem considers both the vehicle's actuation limits and the lateral and longitudinal forces acting on the car modeled through the Pacejka's magic formula and a simple drivetrain model. Furthermore, the approach allows to safely race on a track populated by static obstacles generating collision-free trajectories and tracking them while enhancing the lap timing performance. Gazebo simulations using the F1/10 simulator showcase the feasibility and validity of the proposed control strategy. The code is released as open-source making it possible to replicate the obtained results.

翻译：本文提出了一种非线性模型预测控制（NMPC）策略，旨在控制用于自主竞速比赛的小比例车辆模型。所提出的控制策略以最小化单圈用时为目标，同时确保车辆维持在赛道边界内。优化问题考虑了车辆的作动器极限，以及通过Pacejka魔术公式与简化传动系统模型建模的轮胎侧向和纵向力。此外，该方法允许车辆在存在静态障碍物的赛道上安全行驶，规划无碰撞轨迹并对其进行跟踪，同时提升单圈计时性能。基于F1/10仿真器的Gazebo仿真验证了所提控制策略的可行性与有效性。相关代码已作为开源资源发布，以便复现所得结果。