This paper deals with the problem of distributedly estimating the state of an LTI plant through an interconnected network of agents. The proposed approach results in an observer structure that incorporates consensus among the agents and that can be distributedly designed, achieving a robust solution with a good estimation performance. The developed solution is based on an iterative decomposition of the plant in the local observable staircase forms. The proposed observer has several positive features compared to recent results in the literature, which include milder assumptions on the network connectivity and the ability to set the convergence rate.

Distributed estimation based on multi-hop subspace decomposition / Rodriguez del Nozal, A.; Millan, P.; Orihuela, L.; Seuret, A.; Zaccarian, L.. - In: AUTOMATICA. - ISSN 0005-1098. - 99:(2019), pp. 213-220. [10.1016/j.automatica.2018.10.034]

Distributed estimation based on multi-hop subspace decomposition

Zaccarian L.
2019-01-01

Abstract

This paper deals with the problem of distributedly estimating the state of an LTI plant through an interconnected network of agents. The proposed approach results in an observer structure that incorporates consensus among the agents and that can be distributedly designed, achieving a robust solution with a good estimation performance. The developed solution is based on an iterative decomposition of the plant in the local observable staircase forms. The proposed observer has several positive features compared to recent results in the literature, which include milder assumptions on the network connectivity and the ability to set the convergence rate.
2019
Rodriguez del Nozal, A.; Millan, P.; Orihuela, L.; Seuret, A.; Zaccarian, L.
Distributed estimation based on multi-hop subspace decomposition / Rodriguez del Nozal, A.; Millan, P.; Orihuela, L.; Seuret, A.; Zaccarian, L.. - In: AUTOMATICA. - ISSN 0005-1098. - 99:(2019), pp. 213-220. [10.1016/j.automatica.2018.10.034]
File in questo prodotto:
File Dimensione Formato  
MillanAuto19.pdf

accesso aperto

Tipologia: Pre-print non referato (Non-refereed preprint)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 495.19 kB
Formato Adobe PDF
495.19 kB Adobe PDF Visualizza/Apri
MillanAuto19.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 778.11 kB
Formato Adobe PDF
778.11 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/259051
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 37
  • ???jsp.display-item.citation.isi??? 35
social impact