Brief Recursive identification under scarce measurements - convergence analysis

Authors:
R. Sanchis;P. Albertos
Affiliations:
Departament de Tecnologia, Universitat Jaume I, Campus de Riu Sec, 12071 Castellon, Spain;Departamento de Ingenierıa de Sistemas y Automática (DISA), Universidad Politécnica de Valencia, P.O. Box 22012, E-46071, Valencia, Spain
Venue:
Automatica (Journal of IFAC)
Year:
2002

Citing 1
Cited 3

Brief Paper: Output prediction under scarce data operation: control applications

Automatica (Journal of IFAC)

Parameter estimation algorithms for missing-data systems

ACC'09 Proceedings of the 2009 conference on American Control Conference
Parameter estimation with missing input/output data

ACC'09 Proceedings of the 2009 conference on American Control Conference
Parameter estimation with scarce measurements

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.15

Visualization

Abstract

In this paper, the problem of recursive identification under scarce-data operation is addressed. The control action is assumed to be updated at a fixed rate, while the output is assumed to be measured synchronously with the input update, but with an irregular availability pattern. Under these conditions the use of pseudo-linear recursive algorithms is studied. The main result is the convergence analysis for the case of regular but scarce data availability. The existence of wrong attractors is demonstrated, and a local stability condition of the identification algorithm is derived.