我所金尚泰老师课题组完成的论文《Finite-Time Data-Driven Global Prescribed Performance Vehicle Platoon Resilient Control Against False Data Injection Attacks》于2026-08在《IEEE Internet of Things Journal》正式发表。论文摘要如下：
Abstract: This article presents a finite-time, data-driven, global prescribed performance vehicle platoon resilient control method against false data injection (FDI) attacks. First, by utilizing a dynamic linearization method to design an equivalent linear data model for the nonlinear vehicle platoon system. Within a data-driven framework, we introduce a finite-time performance function (FTPF) to ensure that the follower vehicle tracking error converges to a predefined range within a specified time. Meanwhile, a shifting function is employed to address the strict limitations imposed by the predefined range on the initial values. The introduction of the FTPF and the shifting function improves the tracking accuracy while eliminating the dependence on initial system conditions. Then, to counter FDI attacks, the detection and compensation mechanism is designed to mitigate the influence of FDI attacks on the system. Using the designed compensation mechanism and a data model incorporating prescribed performance, a finite-time, data-driven, global prescribed performance vehicle platoon resilient control method against FDI attacks is proposed. The proposed control method ensures that the vehicle platoon system maintains safe and stable performance under FDI attacks. Finally, the validity of the proposed control method is verified through stability analysis and numerical simulations.
引用信息：Qian Wang, Sen Sun, Qingda Chen, Shangtai Jin, Zhongsheng Hou. Finite-Time Data-Driven Global Prescribed Performance Vehicle Platoon Resilient Control Against False Data Injection Attacks. IEEE Internet of Things Journal, 2026-08-19. DOI: 10.1109/jiot.2026.3725198