Event-triggered Automatic Parking Control for Unmanned Vehicles Against DoS Attacks

This paper investigates an event-triggered model-free adaptive automatic parking (ET-MFAAP) control strategy for unmanned four-wheeled mobile vehicles, particularly addressing the challenge posed by dual-channel denial-of-service (DoS) attacks. The automatic parking control issue is first reformulated as a vehicle body angle tracking problem. A model-free adaptive automatic parking (MFAAP) method is then designed, utilizing only the front wheel steering angle and the vehicle's orientation angle without needing the vehicle's dynamics information. Furthermore, the MFAAP method is extended to an ET-MFAAP method, incorporating an event-triggering communication mechanism to reduce data transmission frequency and input and output compensation strategies to mitigate the impact of DoS attacks on both forward and feedback channels. Finally, the convergence of the control error is theoretically proven, and the effectiveness of the proposed approaches is validated through simulation studies.