Adaptive Consensus Control of Multi-Agent Systems with Dead-Zone Input

In this paper, we study the problem of adaptive consensus control of nonlinear multi-agent systems (MASs) with dead-zone inputs and directed communication topologies. A distributed adaptive fuzzy consensus control technique is devised that effectively lowers the calculation burden of MASs during the communication process by utilizing fuzzy logic systems (FLS) and the backstepping method. Only one fuzzy parameter adaptive law is designed in the iterative process. This reduces the computation of the system to some extent. In addition, the adaptive law is designed to compensate the upper bound of parameters such as dead zone, which completely eliminates the influence of parameters such as dead zone on the system. The stability analysis proves that the consensus tracking error can converge to the neighborhood of the origin; all closed-loop signals are bounded. Finally, the effectiveness of the algorithm is verified by simulation.