Suscripción a Biblioteca: Guest
Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones
Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

Volumen 51, 2019 Volumen 50, 2018 Volumen 49, 2017 Volumen 48, 2016 Volumen 47, 2015 Volumen 46, 2014 Volumen 45, 2013 Volumen 44, 2012 Volumen 43, 2011 Volumen 42, 2010 Volumen 41, 2009 Volumen 40, 2008 Volumen 39, 2007 Volumen 38, 2006 Volumen 37, 2005 Volumen 36, 2004 Volumen 35, 2003 Volumen 34, 2002 Volumen 33, 2001 Volumen 32, 2000 Volumen 31, 1999 Volumen 30, 1998 Volumen 29, 1997 Volumen 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v28.i3-4.100
pages 83-100

An Algorithm for Nonstochastic Identification of Controlled-Object Parameters

Z. Zh. Ametzhanova


The set-theoretic (nonstochastic, guaranteed) approach [1-3, 5-7] is used widely in for solving identification problems when only the sets of the possible values of the object's unknown parameters are specified. This approach allows one to track the evolution of the multidimensional ellipsoidal estimates (approximations) that are guaranteed to contain the object's unknown parameters vector. According to the general schema for solving identification problems by the set-theoretic approach, every ellipsoidal estimate is an intersection of two sets. One of them is the result of processing all past information, and the other corresponds to the latest measurement of the object output. Investigations associated with the construction of set estimates of the unknown parameters vector and the solution of the identification problem in its nonstatic posing are continued in this paper. In contrast with existing algorithms, a new structural variant of the ellipsoidal estimates of the unknown parameters for the case in which several layers that correspond to the latest measurements of the object output intersect with the a-priori ellipsoidal set is proposed here.