A Safe Control Architecture Based on a Model Predictive Control Supervisor for Autonomous Driving

Abstract

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 the 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.

Research and Implementation of Data Fusion in Obstacle Avoidance Control of Mobile Agent

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Robust tube-based LPV-MPC for autonomous lane keeping

“…Besides using MPC as a controller, some papers suggest using MPC for providing safe control architectures (SCA) to guarantee the safety of control inputs from unknown resources. For example, Nezami et al (2021) proposed a SCA in which uses an MPC as the supervisor for an operating controller and the supervisor intervenes only when necessary. Tearle et al (2021) designed a predictive safety filter based on MPC.…”

“…the vehicle, e.g., Nezami et al (2021Nezami et al ( , 2022; Tearle et al (2021); Brüdigam et al (2021).…”