High-Performance Consensus Control in Networked Systems With Limited Bandwidth Communication and Time-Varying Directed Topologies

TLDR

Communication data rates and energy constraints are key factors in coordinating multiagent networks. The study seeks to reduce each agent’s control input update rate without degrading consensus performance. We propose event‑triggered dynamic encoding/decoding algorithms that allow agents to exchange only binary symbolic sequences and adaptively select time‑varying quantization levels in directed, time‑varying digital networks. Analytical results show that the asymptotic convergence rate depends on network size, quantization levels, system parameters, and structure, and that the protocol achieves exponential average consensus with only one‑bit exchanges under a spanning‑tree condition.

Abstract

Communication data rates and energy constraints are two important factors that have to be considered in the coordination control of multiagent networks. Although some encoder-decoder-based consensus protocols are available, there still exists a fundamental theoretical problem: how can we further reduce the update rate of control input for each agent without the changing consensus performance? In this paper, we consider the problem of average consensus over directed and time-varying digital networks of discrete-time first-order multiagent systems with limited communication data transmission rates. Each agent has a real-valued state but can only exchange binary symbolic sequence with its neighbors due to bandwidth constraints. A class of novel event-triggered dynamic encoding and decoding algorithms is proposed, based on which a kind of consensus protocol is presented. Moreover, we develop a scheme to select the numbers of time-varying quantization levels for each connected communication channel in the time-varying directed topologies at each time step. The analytical relation among system and network parameters is characterized explicitly. It is shown that the asymptotic convergence rate is related to the scale of the network, the number of quantization levels, the system parameter, and the network structure. It is also found that under the designed event-triggered protocol, for a directed and time-varying digital network, which uniformly contains a spanning tree over a time interval, the average consensus can be achieved with an exponential convergence rate based on merely 1-b information exchange between each pair of adjacent agents at each time step.