Adaptive Prescribed-Time Control of Switched Nonlinear Systems With False Data Injection Attacks

In this study, a novel adaptive resilient control scheme is proposed to solve the prescribed-time stabilization problem of switched nonlinear systems under false data injection (FDI) attacks. A switched nonlinear state observer (SNSO) is designed to reconstruct unmeasurable system states. Additionally, a novel coordinate transformation and a Nussbaum function are introduced to address the challenges posed by FDI attacks on feedback control channels. The command filter is incorporated into the backstepping control framework, resulting in an adaptive resilient controller to ensure the stability and robustness of the system. Compared with the existing stability results of switched nonlinear systems, this study introduces an innovative prescribed-time scale transformation function into the SNSO and the adaptive resilient controller, thereby yielding a more relaxed criterion for user-defined settling time in the absence of prior information. The proposed piecewise switched adaptive laws reduce the conservatism of the designed controller in the presence of arbitrary switching. Finally, the feasibility of the proposed control theory is validated via simulations.