Stochastic Consensus Control of Second-order Nonlinear Multiagent Systems with External Disturbances

A distributed consensus control method is developed in this paper for second-order nonlinear multi-agent systems (MASs) with external stochastic disturbances. By utilizing the graph theory, the stochastic theory, control technique and linear matrix inequality method, sufficient conditions are derived to guarantee the convergence to mean-square exponential consensus for strongly connected proximity networks and proximity networks with directed spanning trees, respectively. Particularly, using such a methodology, a detailed distributed consensus controller design procedure is provided for networked Euler-Lagrange systems, which are often used in mechanical engineering processes. Finally, the effectiveness of the proposed consensus control method is illustrated by numerical simulations on networked Euler-Lagrange systems.