Adaptive consensus of multi-agent systems under quantized measurements via the edge Laplacian

This paper investigates consensus problems for a first-order nonlinear multi-agent system with unknown non-identical parameters when quantized measurements are available. We explore the utility of edge Laplacian for designing adaptive consensus protocol with quantized state information. A tree structure plays an important role in designing adaptive control with quantized information. Then, all agents achieve consensus mainly based on tree edges information. The proposed protocol has the advantage of using an equivalent simpler graph to avoid the redundant edge information in the cycle structure of the graph. Furthermore, when the multi-agent systems have unknown identical control directions, a Nussbaum-type item is used in the protocol for each agent to seek control direction adaptively and cooperatively. Finally, simulation examples are given to illustrate the effectiveness of the proposed method in this article.