Second-order consensus seeking in directed networks of multi-agent dynamical systems via generalized linear local interaction protocols

This paper focuses on the analytical study of final consensus convergence state of multi-agent dynamical systems by using a kind of generalized linear local interaction protocols. All the agents in the fixed directed network topology are governed by double-integrator dynamics. Almost all the existing linear local interaction consensus protocols can be considered as special cases of the present paper. By combining the algebraic graph theory and the matrix theory, some necessary and sufficient conditions are derived for reaching the second-order consensus. Moreover, the finial consensus convergence states of all agents are also be analytically determined. According to the obtained results, it is found that both the linear gains and the eigenvalues of the Laplacian matrix associated with the directed network topology play key roles in reaching consensus. Finally, the effectiveness and correctness of our theoretical findings are demonstrated by some numerical examples.