Recursive Consensus Estimation for Networked Systems With Random Delays: An Edge-Based Event-Triggered Scheme

Abstract

This paper researches recursive consensus filtering in networked systems affected by random transmission delays under edge-based event-triggered schemes. The study introduces a dynamic edge-level triggering rule to streamline data exchange and alleviate the network’s communication burden. The information incompleteness due to delays is address by transforming the time-delayed observation system into an observation system with zero-time delay through virtualization and rearrangement of the observation sequence. Based on this, a novel consensus filter is proposed, with consensus gain parameters optimized through minimizing the upper bound of the estimation error covariance. Ultimately, this research sheds light on innovative strategies for enhancing consensus filtering in networked systems with random transmission delays.