考虑轮胎力耦合约束的智能汽车轨迹跟踪控制算法

Intelligent vehicle trajectory tracking algorithm taking into account tire force coupling constraints

针对在低附着变速工况下,忽略纵、侧向轮胎力耦合约束可能导致轨迹跟踪时车辆失稳问题,提出了一种模型预测控制框架下的考虑轮胎力耦合约束的车辆轨迹跟踪控制方法。首先,通过摩擦圆假设建立纵、侧向轮胎力的耦合关系,并推导与之等效的输入量边界约束,将该问题转化为约束二次规划问题;其次,提出了一种基于交叉方向乘子法的数值求解构型,降低了求解约束优化问题时Karush-Kuhn-Tucker方程的维数,实现了求解加速。仿真结果表明,在低附着变速工况下,所提出的算法能够实现最大0.166 m误差的稳定跟踪;同时数值求解过程最多仅需8次迭代,增强了控制过程的实时性。

Aiming at the problem of vehicle instability in trajectory tracking caused by neglecting the coupling constraint of longitudinal and lateral tire forces under the low-adhesion variable speed condition, a vehicle trajectory tracking control method considering the coupling constraint of tire forces under the model predictive control framework is proposed. Firstly, the coupling relationship between longitudinal and lateral tire forces is established based on the friction circle hypothesis, and the equivalent input boundary constraints are derived to transform the problem into a constrained quadratic programming problem. Then, a numerical solution configuration based on a cross-direction multiplier method is proposed, which reduces the dimension of Karush-Kuhn-Tucker equations when solving the constrained optimization problems to accelerate the solution. Simulation results show that the proposed algorithm can guarantee stable tracking with the maximum error of 0.166 m, and the numerical optimization process needs only eight iterations at most, which enhances the real-time performance of the control process.