Towards Safety: A Dual-Mode Tracking Control on Roads for the Flying Automobile with Limited Preview Information

Tracking control on roads of autonomous and connected flying automobiles (ACFA), is critical for safety, particularly in emergencies. In these situations, the ACFA must either generate its trajectory in real-time (for instance, to execute an evasive maneuver if an obstacle is detected) or obtain trajectory data from external sources. Generally, the ACFA receives this trajectory information as GPS time samples. However, the feedback control scheme must compensate for the ACFA's lateral speed data, which is not directly accessible. In this paper, we propose a dual-mode approach to design a tracking control scheme for an ACFA, which is achieved through three steps: (1) Using limited preview information from GPS waypoint samples, we calculate the trajectory's radii of curvature with “least-square” estimation, (2)we design a linear model predictive control(MPC) with Kalman filter (KF) for high tracking performance, and(3) When high-level control fails, by using errors as the position, heading, and heading rate we design a feedback control strategy with a fixed structure to track the desired trajectory by calculating stabilizing gains. The effectiveness of the proposed methods is demonstrated through virtual simulation results.