Robustness is a major concern when engineers design lateral stability controllers for intelligent vehicles. The system uncertainty derives from the internal parametric perturbation and the external disturbance. The fuzzy set theory is adopted to describe the bound of the uncertainty. Hence the vehicle lateral dynamical system becomes a fuzzy dynamical system. An explicit robust optimal control law is then proposed to ensure the uniform boundedness and uniform ultimate boundedness of the system. The control law is deterministic and is not IF-THEN fuzzy rule based. A two-player cooperative game is established to determine the optimal value of tunable parameters. The cost functions of the players are developed based on the system performance and the control cost. The Pareto optimal is then obtained using the cooperative game theory. The effectiveness of the proposed method is proven by numerical simulations and Hardware-in-the-loop (HIL) experiments. This paper makes a breakthrough by casting the cooperative game theory and the fuzzy set theory into vehicle lateral stability control.

当工程师为智能车辆设计横向稳定性控制器时，鲁棒性是一个主要问题。系统不确定性来自内部参数扰动和外部扰动。采用模糊集理论来描述不确定性的界限。因此，车辆横向动力系统成为一个模糊动力系统。然后提出了一个明确的鲁棒最优控制律，以确保系统的统一有界和统一的最终有界。控制律是确定性的，不是基于 IF-THEN 模糊规则的。建立一个两人合作博弈来确定可调参数的最优值。参与者的成本函数是基于系统性能和控制成本开发的。然后使用合作博弈论获得帕累托最优。数值模拟和硬件在环 (HIL) 实验证明了所提出方法的有效性。本文将合作博弈论和模糊集理论应用于车辆横向稳定性控制，取得了突破性进展。