Quantized Consensus of Multiagent Systems by Event-Triggered Control

Ji Ma, Lu Liu, Haibo Ji, Gang Feng

Abstract: This paper investigates the quantized consensus problem of general linear multiagent systems (MASs) by event-triggered control. A novel event-triggered distributed control protocol is proposed based on a new dynamic quantizer. Compared with periodical sampling for most existing works on quantized consensus, the proposed event-triggered control approach can significantly save communication and thus energy resource. It is shown that with the proposed distributed control protocol quantized consensus of the concerned MAS can be achieved, and the Zeno behavior and continuous monitoring of the neighbors' states are avoided. Moreover, it is shown that the required number of the quantization levels of the new quantizer remains small even if the number of the agents in the MAS is large. Three simulation examples are given to illustrate the effectiveness of the proposed consensus protocol.