Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm

The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. The identification of model structure for a jacketed continuous stirred tank reactor or CSTR was taken as case study. The analysis showed that...

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Main Authors: Ahmad, R., Jamaluddin, H., Hussain, M. A.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers 2002
Subjects:
Online Access:http://eprints.utm.my/7091/
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author Ahmad, R.
Jamaluddin, H.
Hussain, M. A.
author_facet Ahmad, R.
Jamaluddin, H.
Hussain, M. A.
author_sort Ahmad, R.
building UTeM Institutional Repository
collection Online Access
description The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. The identification of model structure for a jacketed continuous stirred tank reactor or CSTR was taken as case study. The analysis showed that the proposed genetic algorithm provides an efficient way of determining the model structure of unknown nonlinear systems.
first_indexed 2025-11-15T20:57:24Z
format Conference or Workshop Item
id utm-7091
institution Universiti Teknologi Malaysia
institution_category Local University
last_indexed 2025-11-15T20:57:24Z
publishDate 2002
publisher Institute of Electrical and Electronics Engineers
recordtype eprints
repository_type Digital Repository
spelling utm-70912017-08-27T07:17:41Z http://eprints.utm.my/7091/ Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm Ahmad, R. Jamaluddin, H. Hussain, M. A. TJ Mechanical engineering and machinery The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. The identification of model structure for a jacketed continuous stirred tank reactor or CSTR was taken as case study. The analysis showed that the proposed genetic algorithm provides an efficient way of determining the model structure of unknown nonlinear systems. Institute of Electrical and Electronics Engineers 2002 Conference or Workshop Item PeerReviewed Ahmad, R. and Jamaluddin, H. and Hussain, M. A. (2002) Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm. In: IEEE International Conference on Systems, Man and Cybernetics, 6-9 Oct. 2002, Yasmine Hammamet, Tunisia. https://dx.doi.org/10.1109/ICSMC.2002.1176409
spellingShingle TJ Mechanical engineering and machinery
Ahmad, R.
Jamaluddin, H.
Hussain, M. A.
Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title_full Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title_fullStr Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title_full_unstemmed Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title_short Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
title_sort multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
topic TJ Mechanical engineering and machinery
url http://eprints.utm.my/7091/
http://eprints.utm.my/7091/