ODEFTC: Optimal Distributed Estimation based on Fixed-Time Consensus

Perez-Salesa, Irene (Universidad de Zaragoza) ; Aldana-López, Rodrigo (Universidad de Zaragoza) ; Sagüés, Carlos (Universidad de Zaragoza)

Resumen: Distributed state estimation has been a significant research topic in recent years due to its applications for multi-robot and large-scale systems. Several approaches have been proposed in the context of continuous-time systems with stochastic noise, with limitations regarding observability, assumptions on the noise bounds, or requirements to pre-compute auxiliary global information offline. Moreover, many of these approaches are suboptimal with respect to a centralized implementation, and optimal proposals only apply to time-invariant systems. The present work proposes the ODEFTC algorithm for distributed state estimation based on fixed-time consensus. The proposal computes state estimates and corresponding covariance matrices online, making it suitable for time-variant systems. We verify the stability of the proposal through formal analysis, and we show that the optimal centralized solution, given by the Kalman-Bucy filter, can be recovered asymptotically. Additionally, we provide numerical results and an in-depth statistical and numerical discussion to show the advantages of our proposal against other approaches in the literature.

Idioma: Inglés

DOI: 10.1016/j.inffus.2024.102783

Año: 2024

Publicado en: Information Fusion 116 (2024), 102783 [13 pp.]
ISSN: 1566-2535

Factor impacto JCR: 15.5 (2024)

Categ. JCR: COMPUTER SCIENCE, THEORY & METHODS rank: 3 / 147 = 0.02 (2024) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 4 / 204 = 0.02 (2024) - Q1 - T1

Factor impacto SCIMAGO: 4.128 - Hardware and Architecture (Q1) - Software (Q1) - Signal Processing (Q1) - Information Systems (Q1)

Tipo y forma: Article (Published version)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)