Abstract: The message processing and data packet loss of the automotive CAN network would cause the time delay effect of the automotive control system, thereby affecting the accuracy of the vehicle dynamics control. In order to solve this problem, a vehicle yaw stability control strategy was proposed based on robust model predictive control. First, the message delay characteristics of CAN network was analyzed, and a multicellular time-delay model was built to describe the parametric uncertainty. A robust model predictive controller containing uncertain parameters was designed to improve the anti-interference ability of the active safety controller. In addition, the comprehensive solution scheme of the variable time-domain robust optimal control law was also studied based on the asymptotically stable invariant ellipse set to improve the online solution efficiency, and meanwhile to balance the robustness and optimality of the system control. The results show that the proposed control strategy can resist the parameter uncertainty induced by the CAN network, alleviate the conservativeness of the robust control algorithm, and improve the active safety performance of the vehicle.