Robust $H_{\infty}$ Control Based on EID Estimator and PETM for Network-Based Autonomous Vehicles' Path Tracking

This research paper examines resilient <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H_{\infty}$</tex> path-tracking control for networked autonomous vehicles (AVs) facing unforeseen disturbances, packet loss, and delays. A developed robust control technique, integrating an equivalent-input-disturbance (EID) estimator, improves system reliability by facilitating the rejection of unidentified disturbances. The method ensures precise path-tracking, increased system speed, and reduced data transfer and energy consumption. A periodic event-triggered mechanism based on state observers (PETM-SO) further optimizes resource utilization. The system, employing EID, PETM-SO, and AVs model-based robust <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H_{\infty}$</tex> control, ensures stability via Lyapunov-Krasovskii theory with LMIs, achieving asymptotic stability against unknown disturbances. Simulation validates the efficacy and resilience of the proposed control approach.