论文标题
基于强大模型预测控制的安全控制架构，用于自动驾驶
A Safe Control Architecture Based on Robust Model Predictive Control for Autonomous Driving
论文作者
论文摘要
本文提出了一个可靠的安全控制体系结构（RSCA），以进行安全否决。在有界干扰的情况下，要控制的系统是车辆。 RSCA由两个部分组成：主管MPC和一个控制器MPC。主管和控制器都是管MPC（TMPC）。主管MPC在每个步骤中都提供了操作控制器和备份控件输入的安全证书。在预测操作控制器的不安全操作之后，控制器MPC接管了系统。在本文中，提出了一种计算终端集的方法，该方法可抵抗道路弯曲的变化并迫使车辆达到安全参考。此外，本文提供了两个重要的证据。首先，证明备用控制输入可以安全地应用于系统，以将车辆带到安全状态。接下来，证明了RSCA的递归可行性。通过模拟一些避免障碍的情况，可以确认所提出的RSCA的有效性。
This paper proposes a Robust Safe Control Architecture (RSCA) for safe-decision making. The system to be controlled is a vehicle in the presence of bounded disturbances. The RSCA consists of two parts: a Supervisor MPC and a Controller MPC. Both the Supervisor and the Controller are tube MPCs (TMPCs). The Supervisor MPC provides a safety certificate for an operating controller and a backup control input in every step. After an unsafe action by the operating controller is predicted, the Controller MPC takes over the system. In this paper, a method for the computation of a terminal set is proposed, which is robust against changes in road curvature and forces the vehicle to reach a safe reference. Moreover, two important proofs are provided in this paper. First, it is shown that the backup control input is safe to be applied to the system to lead the vehicle to a safe state. Next, the recursive feasibility of the RSCA is proven. By simulating some obstacle avoidance scenarios, the effectiveness of the proposed RSCA is confirmed.
