Finite‐Time Adaptive Resilient Control With Prescribed Performance for Uncertain Nonlinear Systems Under False Data Injection and Actuator Faults

In this article, we present a novel adaptive resilient control strategy for a class of uncertain strict‐feedback nonlinear cyber‐physical systems (CPSs) suffering false data injection (FDI) and actuator faults. In contrast to most studies on nonlinear systems, the unknown state‐dependent gains are considered during system modeling. By formulating convergence‐region‐related piecewise functions, we construct a novel Lyapunov candidate. Then, an adaptive resilient controller, which is proved to guarantee both prescribed performance and finite‐time stability of this system, is subsequently developed using the dynamic surface control (DSC) technique. Specifically, Nussbaum functions and fuzzy logic systems (FLSs) are introduced to address the adverse effects induced by FDI and actuator faults. Through rigorous analysis, it is demonstrated that all signals within the closed‐loop system are semi‐globally bounded, and the state errors can be constrained within any predefined negative exponential function under appropriate parameters. In the end, the feasibility of this control strategy is verified through a simulation based on wing rock dynamics.