Resilient Trajectory Tracking Static Output-Feedback Control for Automated Vehicles under Denial-of-Service Attacks

The safety and reliability of autonomous vehicles are critically linked to network communication quality. Consequently, threats such as Denial-of-Service attacks pose significant risks by disrupting communication between essential components and jeopardizing driving safety. This article presents a robust trajectory tracking control method resilient to such attacks. Utilizing a Linear Parameter–Varying control framework, the method effectively addresses time-varying vehicle speeds and incorporates a norm-bounded strategy to manage tire behavior uncertainties. By employing a Static Output-Feedback scheme, it avoids the need of costly sensors while maintaining a straightforward control structure suitable for real-time implementation. Using Lyapunov’s method, we analyze the system stability under attack conditions, ensuring the controller remains robust against disturbances. The design of the resilient controller is formulated as a convex optimization problem with Linear Matrix Inequalities constraints. The effectiveness of the proposed controller is validated through co-simulation in MATLAB/CarSim®, where it outperforms several state-of-the-art controllers across different driving scenarios, maintaining consistent tracking performance despite varying attack severity levels.