Distributed moving horizon estimation with event-triggered mechanism for complex networked systems subject to packet dropouts and quantization

• Published in: Journal of the Franklin Institute Vol. 362; no. 15; p. 107988
• Main Authors: Afshari, Melika, Rahmani, Mehdi
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2025
• Subjects: Complex networks; Event-triggered mechanism; Moving horizon estimation; Packet dropout; Quantization; Quantization; Event-triggered mechanism; Moving horizon estimation; Complex networks; Packet dropout
• ISSN: 0016-0032
• DOI: 10.1016/j.jfranklin.2025.107988

•A distributed event-based MHE approach is proposed for LTV complex networks.•The networked system is subject to quantized measurements and packet dropouts.•Stochastic min-max optimization is driven to achieve closed-form solutions for each local esti-mator.•Stability analysis ensures the exponential boundedness of the estimation error. This study investigates the problem of distributed moving horizon estimation (DMHE) in time-varying complex networks decomposed into coupled subsystems. Subsystem measurements are quantized and are subject to packet dropouts in the communication network. To reduce communication overhead, an event-triggered mechanism is proposed to regulate the transmission of measurements and estimates within each subsystem. The primary objective of this research is to derive a closed-form analytical solution to the MHE problem in complex networks. To this end, a stochastic robust cost function is designed to formulate a regularized robust least-squares (RRLS) problem to obtain the optimal estimator. Furthermore, the proposed event-triggered communication scheme ensures the exponential boundedness of the estimation error, regardless of the degree of quantization or packet loss. Simulation results validate the effectiveness and performance of the proposed filtering approach compared with the most relevant methods in the literature.