1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods

This work deals with a physical one- and two-dimensional (1D and 2D) parameters estimation of a filtration process of slurry, the second stage of phosphoric acid manufacture. This study focuses on recursive least square and instrumental variable techniques applied to the (1D) and (2D) models. The mo...

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Main Authors: S. Ben Mohamed, B. Boussaid, M. N. Abdelkrim, C. Tahri
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:Automatika
Subjects:
Online Access:http://dx.doi.org/10.1080/00051144.2018.1498212
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spelling doaj-0dcab8adc29f48f8a49a60992ca83c0f2020-11-24T22:14:51ZengTaylor & Francis GroupAutomatika0005-11441848-33802018-01-0159110411910.1080/00051144.2018.149821214982121D and 2D parameter estimation of a rotary drum filter based on RLS and IV methodsS. Ben Mohamed0B. Boussaid1M. N. Abdelkrim2C. Tahri3University of Gabes National School of Engineers of Gabes ModelingUniversity of Gabes National School of Engineers of Gabes ModelingUniversity of Gabes National School of Engineers of Gabes ModelingTunisian Chemical Group, Factory of SkhiraThis work deals with a physical one- and two-dimensional (1D and 2D) parameters estimation of a filtration process of slurry, the second stage of phosphoric acid manufacture. This study focuses on recursive least square and instrumental variable techniques applied to the (1D) and (2D) models. The model of the rotary drum filter is based on different physical laws involved in the filtration phase in order to get a simulator of the filtration process. Besides, many physical parameters rise in the system model and effect enormously the efficiency which should be modelled with precision such as permeability, porosity and viscosity. We use a constructive realization procedure for (2D) systems which may lead to a Fornasini–Marchesini local state-space model to describe the dynamic of the system states.http://dx.doi.org/10.1080/00051144.2018.1498212Filtration(1D) system(2D) system(FM-II) model(1D) RLS identificationIV identification(2D) RLS identification
collection DOAJ
language English
format Article
sources DOAJ
author S. Ben Mohamed
B. Boussaid
M. N. Abdelkrim
C. Tahri
spellingShingle S. Ben Mohamed
B. Boussaid
M. N. Abdelkrim
C. Tahri
1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
Automatika
Filtration
(1D) system
(2D) system
(FM-II) model
(1D) RLS identification
IV identification
(2D) RLS identification
author_facet S. Ben Mohamed
B. Boussaid
M. N. Abdelkrim
C. Tahri
author_sort S. Ben Mohamed
title 1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
title_short 1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
title_full 1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
title_fullStr 1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
title_full_unstemmed 1D and 2D parameter estimation of a rotary drum filter based on RLS and IV methods
title_sort 1d and 2d parameter estimation of a rotary drum filter based on rls and iv methods
publisher Taylor & Francis Group
series Automatika
issn 0005-1144
1848-3380
publishDate 2018-01-01
description This work deals with a physical one- and two-dimensional (1D and 2D) parameters estimation of a filtration process of slurry, the second stage of phosphoric acid manufacture. This study focuses on recursive least square and instrumental variable techniques applied to the (1D) and (2D) models. The model of the rotary drum filter is based on different physical laws involved in the filtration phase in order to get a simulator of the filtration process. Besides, many physical parameters rise in the system model and effect enormously the efficiency which should be modelled with precision such as permeability, porosity and viscosity. We use a constructive realization procedure for (2D) systems which may lead to a Fornasini–Marchesini local state-space model to describe the dynamic of the system states.
topic Filtration
(1D) system
(2D) system
(FM-II) model
(1D) RLS identification
IV identification
(2D) RLS identification
url http://dx.doi.org/10.1080/00051144.2018.1498212
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