Quantized consensus for nonlinear multi-agent system based on edge Laplacian

In this paper, a consensus problem for nonlinear multi-agent systems is considered in the presence of quantized measurement. The dynamic of each agent is first-order linearly parameterized system with non-identical unknown parameter. It is known that the consensus problem for linear multi-agent systems can be solved based on node state information, and equivalent results can be obtained via edge Laplancian approach. However, such an “equivalent phenomenon” does not necessarily apply to nonlinear multi-agent systems with quantized measurement. Thus, to overcome the problem, we will explore the utility of edge Laplacian for designing adaptive consensus protocol with quantized state information. The results of this work will show that the edge Laplacian provides a new perspective for the control design. In addition, some interesting results based on the information of tree edges of the graph is proposed to apply the adaptive consensus protocol for nonlinear multi-agent systems with quantized information. Finally, simulation examples are given to illustrate the effectiveness of the proposed method in this article.