Modeling uncertainties are a major concern in vehicle path tracking control. As a practical engineering system, the uncertainties in vehicle lateral dynamics can be time-varying while bounded and have certain distributions wherein. The fuzzy set theory can effectively describe system uncertainties in terms of boundary and distribution. Contrary to fuzzy logic-based approaches, this article puts forward an explicit multiparameter optimal robust control law to ensure the uniform boundedness and ultimate uniform boundedness of the closed-loop path tracking dynamical system. Then, the tracking performance as well as the control cost is quantified as cost functions using fuzzy set theories. Finally, an optimization problem is established in the content of cooperative game to seek the optimal values for the tunable parameters. Simulations are conducted using CarSim and Simulink under double lane change and serpentine driving conditions. The results show that the proposed robust optimal control exhibits superior tracking performance.

建模不确定性是车辆路径跟踪控制中的主要问题。作为实际的工程系统，车辆横向动力学的不确定性在有界的时候可以是时变的，并且具有一定的分布。模糊集理论可以根据边界和分布有效地描述系统的不确定性。与基于模糊逻辑的方法相反，本文提出了一种明确的多参数最优鲁棒控制律，以确保闭环路径跟踪动力学系统的一致有界和最终一致有界。然后，使用模糊集理论将跟踪性能以及控制成本量化为成本函数。最后，在合作博弈的内容中建立了一个优化问题，以寻求可调整参数的最优值。使用CarSim和Simulink在双车道变更和蜿蜒行驶条件下进行仿真。结果表明，所提出的鲁棒最优控制具有优良的跟踪性能。