Observer-Based Adaptive Fuzzy Consensus Control of Nonlinear Multi-Agent Systems Encountering Deception Attacks

This paper investigates the fuzzy adaptive output-feedback consensus control problem for nonlinear multi-agent systems (MASs) with network communication encountering deception attacks. Fuzzy logic systems (FLSs) are used to approximate unknown nonlinear functions, and a novel fuzzy state observer is established to estimate the states of encountered deception attacks. For the case of unknown time-varying gains caused by deception attacks, a projection operator-based compensation mechanism is designed. Consequently, under the framework of adaptive backstepping, a novel adaptive fuzzy output-feedback consensus control method is proposed. The proposed control method can not only ensure that all signals remain bounded, but also make all followers maintain consensus with the trajectory of the leader. Finally, the simulation results are given to confirm the effectiveness of the proposed control scheme.