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, Mohd Azlan
Format: Conference or Workshop Item
Language:English
Published: 2002
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Online Access:http://eprints.um.edu.my/7078/1/Multivariable_system_identification_for_dynamic_discrete-time_nonlinear_system_using_genetic_algorithm.pdf
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spelling my.um.eprints.70782021-02-10T03:17:24Z http://eprints.um.edu.my/7078/ Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm Ahmad, R. Jamaluddin, H. Hussain, Mohd Azlan TA Engineering (General). Civil engineering (General) TP Chemical technology 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. 2002 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/7078/1/Multivariable_system_identification_for_dynamic_discrete-time_nonlinear_system_using_genetic_algorithm.pdf Ahmad, R. and Jamaluddin, H. and Hussain, Mohd Azlan (2002) Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm. In: 2002 IEEE International Conference on Systems, Man and Cybernetics, 2002, Yasmine Hammamet. http://www.scopus.com/inward/record.url?eid=2-s2.0-0037731329&partnerID=40&md5=ee1678345723d582d910a2809d82c0c3
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
TP Chemical technology
spellingShingle TA Engineering (General). Civil engineering (General)
TP Chemical technology
Ahmad, R.
Jamaluddin, H.
Hussain, Mohd Azlan
Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
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.
format Conference or Workshop Item
author Ahmad, R.
Jamaluddin, H.
Hussain, Mohd Azlan
author_facet Ahmad, R.
Jamaluddin, H.
Hussain, Mohd Azlan
author_sort Ahmad, R.
title 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_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_sort multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm
publishDate 2002
url http://eprints.um.edu.my/7078/1/Multivariable_system_identification_for_dynamic_discrete-time_nonlinear_system_using_genetic_algorithm.pdf
http://eprints.um.edu.my/7078/
http://www.scopus.com/inward/record.url?eid=2-s2.0-0037731329&partnerID=40&md5=ee1678345723d582d910a2809d82c0c3
_version_ 1691733423118352384
score 13.214268