  The work done in this paper, proposes a complex Laplacian-based distributed
control scheme for convergence in the multi-agent network. The proposed scheme
has been designated as cascade formulation. The proposed technique exploits the
traditional method of organizing large scattered networks into smaller
interconnected clusters to optimize information flow within the network. The
complex Laplacian-based approach results in a hierarchical structure, with
formation of a meta-cluster leading other clusters in the network. The proposed
formulation enables flexibility to constrain the eigen spectra of the overall
closed-loop dynamics, ensuring desired convergence rate and control input
intensity. The sufficient conditions ensuring globally stable formation for
proposed formulation are also asserted. Robustness of the proposed formulation
to uncertainties like loss in communication links and actuator failure has also
been discussed. The effectiveness of the proposed approach is illustrated by
simulating a finitely large network of thirty vehicles.
