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DYNAMIC ESTIMATION AND UNCERTAINTY QUANTIFICATION FOR MODEL-BASED CONTROL OF DISCRETE SYSTEMS

DYNAMIC ESTIMATION AND UNCERTAINTY QUANTIFICATION FOR MODEL-BASED CONTROL OF DISCRETE SYSTEMS

Authors :
Belmiro P.M. Duarte
João F.M. Gândara
Nuno M.C. Oliveira
Source :
IFAC Proceedings Volumes. 39:585-590
Publication Year :
2006
Publisher :
Elsevier BV, 2006.

Abstract

This paper presents an approach to estimate the outputs and the uncertainty associated to the forecast for discrete dynamic systems represented by state-space models. The complete strategy includes three steps: 1. process identification based on a data sample; 2. estimation of the current process state based on the information available during a moving past horizon, which may contain lack of observations; 3. forecast of process states, process outputs and uncertainty along the future horizon. This procedure can be incorporated in control strategies that explicitly consider model uncertainty.

Details

ISSN :
14746670
Volume :
39
Database :
OpenAIRE
Journal :
IFAC Proceedings Volumes
Accession number :
edsair.doi...........fcc5b47ab6f3ddbf60d1ad3dc0c93b99
Full Text :
https://doi.org/10.3182/20060402-4-br-2902.00585