Security Cooperative Path-Tracking for Connected Vehicle Swarm Resilient to Dual-Channel Deception Attacks

This paper investigates the security path-tracking control problem for the connected vehicle swarm with uncertain dynamics, specifically emphasizing its resilience against dual-channel deception attacks. To ensure the security and reliability of data transmission against such cyber threats, a novel attack compensation mechanism is proposed to eliminate the impact of deception attacks by securing data transmission against signal tampering in both sensor-controller and controller-actuator channels. We design a fuzzy state estimator to reconstruct uncompromised signals from tampered data, thereby constructing a security control strategy resilient to deception attacks. Considering practical network bandwidth constraints, a fuzzy adaptive dynamic event-triggered path-tracking control strategy is developed, which integrates the proposed attack compensation mechanism and state estimator to mitigate the impact of cyber attacks. Sufficient conditions are established to guarantee the security path-tracking performance. With the Lyapunov stability theory, it is proved that error systems are uniformly ultimately bounded, and the Zeno phenomenon can be effectively prevented. Simulation results validate the effectiveness of the theoretical approach.