Output prediction under scarce data operation: Control applications
type: Item
instance of: scholarly article
title: Output prediction under scarce data operation: Control applications
zbMATH Open document ID: 0935.93058
DOI: 10.1016/S0005-1098(99)00078-3
published in: Automatica
publication date: 2000-04-24T00:00:00Z
review text: The paper deals with the estimation of outputs of a process from scarcely sampled measurements or a missing data sampling pattern, assuming that the process model is known. A wide range of methods to predict estimations of unmeasured outputs in missing-data situations are studied. The main result is the presentation of an algorithm that uses the difference equation of the process, replacing the unknown past values with estimates when necessary.
reviewed by: Bernd Mathiszik
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93C57
Mathematics Subject Classification ID: 93C41
zbMATH DE Number: 1356087
zbMATH Keywords: output estimation
zbMATH Keywords: state estimation
zbMATH Keywords: parameter estimation
zbMATH Keywords: missing data
zbMATH Keywords: unconventional sampling
author: Pedro Albertos
author: Roberto Sanchis
author: Antonio Sala
MaRDI profile type: Publication
full work available at URL: s0005-1098(99)00078-3
OpenAlex ID: W2284499571
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description: scientific article; zbMATH DE number 1356087