Trajectory Tracking for an Adaptive Cruise Control System Using Differential Flatness and Gaussian Processes

In this paper, we explain how differential flatness combined with Gaussian Processes can be applied for the adaptive cruise control system under external, unknown dynamics, to attain accurate trajectory tracking. The proposed approach employs differential flatness for controller design, along with Gaussian Processes to estimate the unknown components in the dynamics. In order to ensure robustness to this data-driven technique, a robust control law is also introduced, that further exploits the Gaussian Process framework. In the recent publication [12], we showed the effectiveness of the proposed control methodology for set-point regulation. In the current paper, we generalize it to trajectory tracking and show numerically that the error dynamics converge to zero.