Quantized consensus for multi-agent networks with directed switching topologies

This paper studies the quantized consensus problem for a group of agents over directed networks with switching topologies. We propose an effective distributed protocol with an adaptive finite-level uniform quantized strategy, under which consensus among agents can be guaranteed without utilizing existing symmetry error-compensation method. We conduct convergence analysis based on related input-to-output stability result, which avoids the typical common left eigenvector requirement for the existence of common quadratic lyapunov function. In particular, it is established that, provided the duration of link failure in the directed network is bounded, then at each time instant, each agent (may be nonreciprocally) sends 5-level quantization information to each of its intimate neighbors, together with 3-level quantization information to itself, which suffices for ensuring consensus with an exponential convergence rate. The proposed quantized protocol features little communication protocol overhead and fits well into the digital network framework.