Event-Triggered Cooperative Adaptive Neural Control for Cyber–Physical Systems With Unknown State Time Delays and Deception Attacks

作者：Xin Wang, Yuhao Zhou, Lü Yang · 发表于：IEEE Transactions on Systems Man and Cybernetics Systems · 年份：2022 · DOI：10.1109/tsmc.2022.3228798 · 被引用次数：45 · 研究领域：Distributed Control Multi-Agent Systems、Advanced Memory and Neural Computing、Neural Networks Stability and Synchronization

In this article, an event-triggered adaptive control strategy is proposed to achieve the leaderless-following consensus for a class of cyber–physical systems under the direct topology. Because the deception attacks, state time delay, and unknown external disturbance appear simultaneously, the existing method is hard to apply directly. The difficulty of this issue lies in that the actual system states are unavailable and control efficiencies are unknown, which caused by the deception attack. So as to tackle these knotty problems, the Nussbaum gain functions are employed to replace the control gains, and the available compromised system variables are applied in the controllers. In addition, the proposed disturbance observer based on the compromised state further improves the robustness of the system. To eliminate the influence of state time delays, the appropriate Lyapunov–Krasovskii functionals are used in the backstepping design process. Moreover, the computation and communication burden is dramatically decreased than by adopting the event-triggered mechanism and less adaptive laws. The boundedness of all signals in the closed-loop system is guaranteed via the Lyapunov stability theorem. Finally, the simulation results are provided to demonstrate the availability of the proposed control strategy.