Global Fuzzy Adaptive Consensus Control of Unknown Nonlinear Multiagent Systems

Abstract

This paper investigates the global consensus problems for the first-order and second-order unknown nonlinear multiagent systems (MASs) with uncertain input disturbance. Fuzzy logic systems are applied to solve the global consensus problem for unknown nonlinear MASs. A fully distributed adaptive fuzzy control is designed to enable followers asymptotically to track the leader without using any dynamics of the leader. The global consensus conditions are also derived for the first-order and second-order unknown MASs, which overcomes the drawback of the semiglobal consensus in existing literature. It is worth mentioning that the proposed approach can greatly alleviate the computation burden because it only needs to update a few parameters. An efficient framework is also given to achieve the global formation control of the second-order unknown nonlinear MAS with an undirected connected graph. Finally, four simulated examples are given to illustrate the effectiveness of the proposed control protocols.