Adaptive Fuzzy Control for State-Constrained Nonlinear Cyber-Physical Systems With Unmodeled Dynamics Against Malicious Attacks

This article investigated the tracking control problem for a category of state-constrained high-order uncertain nonlinear cyber-physical systems (CPSs) with unmodeled dynamics, which are subject to malicious attacks launched in controller-actuator (C-A) channel. Combining the backstepping method, dynamic surface control (DSC) approach and fuzzy logic systems (FLSs), a novel adaptive fuzzy tracking control strategy is developed, where a one to one mapping is brought in to transform the state-constrained CPSs to be the ones without state constraints and a dynamical signal is introduced to cope with the unmodeled dynamics. The proposed control strategy is not only independent of the exact system model, but also accommodates the external disturbances, unmodeled dynamics and malicious attacks. In particular, the developed control strategy can make sure that the output tracking error enters a predefined small neighborhood of the origin, and guarantee all the signals of the resulting closed-loop system satisfy the corresponding state constraints during the total operation, where the tracking accuracy level are known and can be preconfigured by selecting the design parameters appropriately. Ultimately, a representative simulation is provided to illustrate the validity and superiority of the proposed control scheme.