An Event-Triggered Average Consensus Algorithm with Performance Guarantees for Distributed Sensor Networks

Amir Amini; Amir Asif; Arash Mohammadi

ICASSP 2018accepted0 citations

An Event-Triggered Average Consensus Algorithm with Performance Guarantees for Distributed Sensor Networks

Abstract

This paper proposes a distributed guaranteed-performance event-triggered average consensus (GP-ETAC) algorithm for multi-agent/sensor networks. The proposed GP-ETAC approach is distributed and event-triggered in the sense that the agents selectively limit their transmissions to local neighbourhoods when certain triggering conditions are satisfied. Using the Lyapunov stability theorem, a novel cost function is optimized to compute consensus design parameters (namely, the overall control gain and local event-triggering thresholds). The proposed cost function provides a structured trade-off between the number of local transmissions and the rate of consensus convergence. The performance of the GP-ETAC approach is evaluated through Monte-Carlo simulations.

BibTeX

@inproceedings{icassp2018_aneventtriggered,
  title = {An Event-Triggered Average Consensus Algorithm with Performance Guarantees for Distributed Sensor Networks},
  author = {Amir Amini and Amir Asif and Arash Mohammadi},
  booktitle = {ICASSP 2018},
  year = {2018}
}