Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/74550
Type: Artigo de periódico
Title: State estimation of batch distillation columns using an extended Kalman filter
Author: Oisiovici, RM
Cruz, SL
Abstract: Composition monitoring and control play an essential role during a batch distillation cycle, but on-line composition analyzers are expensive, difficult to maintain and give delayed responses. Considering the need and lack of a stochastic estimator for batch distillation columns, a discrete extended Kalman filter (EKF) for binary and multicomponent systems has been developed and tested. The aim of the EKF was to provide reliable and real-time column composition profiles from few temperature measurements and easily available information. Accurate composition estimates and fast convergence were obtained, and the EKF has confirmed its ability to incorporate the effects of noise (from both measurement and modeling). The number of sensors and the observation frequency have shown to be important variables in the design of the EKF, especially for systems with fast dynamics. (C) 2000 Elsevier Science Ltd. All rights reserved.
Subject: batch distillation
Kalman filtering
stochastic estimator
discrete systems
inference
nonlinear
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/S0009-2509(00)00088-9
Date Issue: 2000
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
WOS000089334300022.pdf461.68 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.