System identification of an interacting series process for real-time model predictive control

This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model ar...

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Main Authors: M.N., Karsiti, T.C.S., Wibowo, N., Saad
Format: Conference or Workshop Item
Language:English
Published: 2009
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/471/
http://scholars.utp.edu.my/id/eprint/471/1/paper.pdf
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author M.N., Karsiti
T.C.S., Wibowo
N., Saad
author_facet M.N., Karsiti
T.C.S., Wibowo
N., Saad
author_sort M.N., Karsiti
building UTP Institutional Repository
collection Online Access
description This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals. Three practical approaches are used and their performances are compared to obtain the most suitable approach for modeling of such a system. The models are also tested in the real-time implementation of a linear model predictive control. The selected model is able to well reproduce the main dynamic characteristics of gaseous pilot plant in open loop and produces zero steady-state errors in closed loop control system. Several issues concerning the identification process and the construction of MIMO state space model are discussed. © 2009 AACC.
first_indexed 2025-11-13T07:23:23Z
format Conference or Workshop Item
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institution Universiti Teknologi Petronas
institution_category Local University
language English
last_indexed 2025-11-13T07:23:23Z
publishDate 2009
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repository_type Digital Repository
spelling oai:scholars.utp.edu.my:4712017-01-19T08:25:48Z http://scholars.utp.edu.my/id/eprint/471/ System identification of an interacting series process for real-time model predictive control M.N., Karsiti T.C.S., Wibowo N., Saad TK Electrical engineering. Electronics Nuclear engineering This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals. Three practical approaches are used and their performances are compared to obtain the most suitable approach for modeling of such a system. The models are also tested in the real-time implementation of a linear model predictive control. The selected model is able to well reproduce the main dynamic characteristics of gaseous pilot plant in open loop and produces zero steady-state errors in closed loop control system. Several issues concerning the identification process and the construction of MIMO state space model are discussed. © 2009 AACC. 2009 Conference or Workshop Item NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/471/1/paper.pdf M.N., Karsiti and T.C.S., Wibowo and N., Saad (2009) System identification of an interacting series process for real-time model predictive control. In: 2009 American Control Conference, ACC 2009, 10 June 2009 through 12 June 2009, St. Louis, MO. http://www.scopus.com/inward/record.url?eid=2-s2.0-70449640063&partnerID=40&md5=65767b2aefe9805894163de7267fb35b
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
M.N., Karsiti
T.C.S., Wibowo
N., Saad
System identification of an interacting series process for real-time model predictive control
title System identification of an interacting series process for real-time model predictive control
title_full System identification of an interacting series process for real-time model predictive control
title_fullStr System identification of an interacting series process for real-time model predictive control
title_full_unstemmed System identification of an interacting series process for real-time model predictive control
title_short System identification of an interacting series process for real-time model predictive control
title_sort system identification of an interacting series process for real-time model predictive control
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/471/
http://scholars.utp.edu.my/id/eprint/471/
http://scholars.utp.edu.my/id/eprint/471/1/paper.pdf