Yihui Xu , Huiyan Zhang , Yongchao Liu , Ning Zhao , Imre J. Rudas
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DoS-resilient event-triggering control of connected vehicles: An attack-parameter-dependent functional method
This article studies the problem of event-triggering formation tracking control for networked autonomous vehicles in the face of denial-of-service (DoS) attacks. Because of the disruptive nature of DoS attacks on vehicle-to-vehicle communication, the traditional control strategy is difficult to accomplish the task of vehicle formation. To overcome this problem, a resilient distributed dynamic event-triggered control strategy is created to mitigate the impact of attacks on intermittent communication. Meanwhile, to optimize network resource utilization, a novel dynamic event-triggered scheme is designed to significantly reduce the frequency of data updates and transmits in the controller. Subsequently, a novel Lyapunov function is established to rigorously analyze the exponential stability of the vehicle formation system. The function incorporates attack-related time-varying parameters and deals with the artificial delay introduced in the model through an interval correlation function, which significantly reduces conservatism and simplifies the stability analysis process. Finally, the effectiveness of the control strategy is confirmed through a simulation study conducted on the vehicle platoon system.
期刊介绍:
Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions.
Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.