Distributed adaptive output consensus tracking of nonlinear multi-agent systems via state observer and command filtered backstepping

This paper investigates the adaptive fuzzy output consensus tracking control for nonlinear multi-agent systems in the presence of input saturation. The interaction among the agents is described by a directed graph. Firstly, a local fuzzy state estimator is proposed to reconstruct the unmeasured state of each agent. Then, a novel command filtered backstepping based distributed adaptive control law is designed, where theunknown nonlinear dynamics are approximated by using the fuzzy logic system. The proposed control law can guarantee that the output consensus tracking errors converge into a sufficiently small neighborhood of the origin and all signals in the closed-loop system are bounded although the input saturation exists. Simulation results show the effectiveness of the proposed design.