Robust Adaptive Rapid Exponential Stabilization for a Class of Nonlinear Cyber‐Physical Systems Under Denial‐Of‐Service Attacks

ABSTRACT In this paper, we investigate the stabilization problem of a class of uncertain nonlinear cyber‐physical systems (CPSs) under random denial‐of‐service (DoS) attacks with average frequency and duration constraints. This investigation presents a rapid exponential stabilization‐based robust adaptive control (RESRAC) scheme with a corresponding update trigger strategy to improve the robustness of the CPSs against DoS attacks. As a result, the system stability can be guaranteed under DoS attacks of nearly arbitrary intensity as long as the communication is not completely blocked by selecting an appropriate high‐gain parameter offline, and the novel convergence condition obtained in the Lyapunov analysis extends the general convergence condition used in most related studies. To demonstrate the control performance of this control scheme, a numerical example is presented. Additionally, to enhance the applicability of the proposed scheme in practice, an online adjusting RESRAC with a modified update triggering strategy is proposed to mitigate the peaking phenomenon resulting from the high‐gain feedback in the RESRAC. An adjusting algorithm is designed to reduce the conservativeness of the selection of the high‐gain parameters through the online identification of the evolution rate of the system state during the attacked interval. Finally, a numerical simulation is carried out to illustrate the effectiveness and superiority of the proposed online adjusting control scheme.