Self-triggered Consensus of Multi-agent Systems with Quantized Relative State Measurements

Abstract

This paper addresses the consensus problem of first-order continuous-time multi-agent systems over undirected graphs. Each agent samples relative state measurements in a self-triggered fashion and broadcasts the sum of the measurements to its neighbors. Moreover, finite-level dynamic quantizers with zooming-in capability is applied to the measurements. The proposed joint design method of quantization and self-triggered sampling achieves asymptotic consensus without Zeno behaviors. Sampling times are determined explicitly with iterative procedures including the computation of the Lambert function. We introduce a new semi-norm for the consensus analysis of multi-agent systems. A simulation example is provided to illustrate the effectiveness of the proposed protocol.