Adaptive Fuzzy Control for Nonlinear Multiagent Systems Subject to Multiple Constraints Under Deception Attacks

This paper presents an adaptive fuzzy tracking control protocol for a category of uncertain nonlinear multi-agent systems (MASs) subject to deception attacks and multiple constraints (time-varying asymmetry constraints on tracking error and system states). Fuzzy logic systems (FLSs) are employed to approximate the unknown nonlinear dynamics in MASs. Since deception attacks over the sensor network make the actual states of the MASs unavailable, this paper employs the compromised states for feedback control. Based on the relationship between the compromised states and actual states, the problem of satisfying the original state constraints boils down to the new constraints on compromised states. The use of a nonlinear mapping together with the dynamic surface control (DSC) strategy can ensure that the multiple constraints are solved with the constraint boundaries of system output being freely selected by the user, the feasibility requirement on the virtual controller is removed, and the computational explosion is mitigated. Under this control protocol, the tracking performance of MASs subject to deception attacks is achieved, while all constraints are not violated. Ultimately, simulation results verify the effectiveness and advantage of the developed control method.