Optimal averaging time for improving observer accuracy of stochastic dynamical systems
Balaguer, Pedro (Universitat Jaume I)
Ibeas, Asier (Universitat Autònoma de Barcelona)

Data:	2021
Resum:	In the problem of remote estimation by a centralized observer, improvements to the accuracy of observer estimates come at a cost of higher communication bandwidth and energy consumption. In this article we improve observer estimation accuracy by reducing the measurement variance on the sensor node before its transmission to the centralized observer node. The main contribution is to show that measurement variance is a trade-off between dynamical system variance and sensor variance. As a result there is an optimal averaging time that minimizes measurement variance, providing more accurate measurement to the observer. The optimal averaging time is computable by solving a univariate optimization problem.
Drets:	Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets.
Llengua:	Anglès
Document:	Article ; recerca ; Versió sotmesa a revisió
Matèria:	Kalman filter ; Observer ; Optimal averaging time ; Smart sensors ; Stochastic processes ; Wireless sensor networks ; SDG 7 - Affordable and Clean Energy
Publicat a:	ISA Transactions, Vol. 108 (February 2021) , p. 207-219, ISSN 0019-0578

DOI: 10.1016/j.isatra.2020.08.039
PMID: 32948316

Preprint 37 p, 2.2 MB

El registre apareix a les col·leccions:
Articles > Articles de recerca
Articles > Articles publicats