Adaptive Fuzzy Resilient Control Against Unknown Deception Injection Attacks for Pure-Feedback Nonlinear Switched Systems With Intermittent Actuator Faults

This paper is concerned with the adaptive resilient control problem of the pure-feedback nonlinear switched systems with intermittent actuator faults. First, by employing the mean value theorem, the pure-feedback systems under consideration are converted into a category of strict-feedback nonlinear switched systems. Furthermore, by designing new coordinate transformations and Lyapunov functions, an improved adaptive resilient control design is developed, which effectively addresses the issues stemming from sensor deception attacks that obscure the original system information and involve unknown time-varying attack gains. To compensate for the intermittent failures of the actuator, a new adaptive fuzzy resilient controller is developed by co-designing the last virtual control function. Compared to the existing results, the proposed control method not only addresses the resilient control issue of pure-feedback nonlinear switched systems with deception injection attacks but also tackles the control problem of infinite actuator failures. At last, the results from the simulation substantiate the efficiency of the constructed control algorithm.