000147105 001__ 147105
000147105 005__ 20241212141912.0
000147105 0247_ $$2doi$$a10.1016/j.inffus.2024.102783
000147105 0248_ $$2sideral$$a140910
000147105 037__ $$aART-2024-140910
000147105 041__ $$aeng
000147105 100__ $$0(orcid)0000-0002-0283-7344$$aPerez-Salesa, Irene$$uUniversidad de Zaragoza
000147105 245__ $$aODEFTC: Optimal Distributed Estimation based on Fixed-Time Consensus
000147105 260__ $$c2024
000147105 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147105 5203_ $$aDistributed 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.
000147105 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000147105 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000147105 700__ $$aAldana-López, Rodrigo$$uUniversidad de Zaragoza
000147105 700__ $$0(orcid)0000-0002-3032-954X$$aSagüés, Carlos$$uUniversidad de Zaragoza
000147105 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000147105 773__ $$g116 (2024), 102783 [13 pp.]$$pInformation Fusion$$tInformation Fusion$$x1566-2535
000147105 8564_ $$s3163453$$uhttps://zaguan.unizar.es/record/147105/files/texto_completo.pdf$$yVersión publicada
000147105 8564_ $$s2685430$$uhttps://zaguan.unizar.es/record/147105/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000147105 909CO $$ooai:zaguan.unizar.es:147105$$particulos$$pdriver
000147105 951__ $$a2024-12-12-12:43:03
000147105 980__ $$aARTICLE