Recursive least square and fuzzy modelling using genetic algorithm for process control application
A technique for the modelling of nonlinear process control using Recursive Least Square and Takagi-Sugeno Fuzzy System with Genetic Algorithm topology is described. This paper discusses the identification of parameters of the fuzzy sets at the antecedent part and linear model at the consequent part...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2007
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| Online Access: | http://psasir.upm.edu.my/id/eprint/48267/1/Recursive%20least%20square%20and%20fuzzy%20modelling%20using%20genetic%20algorithm%20for%20process%20control%20application.pdf |
| _version_ | 1825929970846793728 |
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| author | Abdul Rahman, Ribhan Zafira Yusof, Rubiyah Khalid, Marzuki |
| author_facet | Abdul Rahman, Ribhan Zafira Yusof, Rubiyah Khalid, Marzuki |
| author_sort | Abdul Rahman, Ribhan Zafira |
| collection | UPM |
| description | A technique for the modelling of nonlinear process control using Recursive Least Square and Takagi-Sugeno Fuzzy System with Genetic Algorithm topology is described. This paper discusses the identification of parameters of the fuzzy sets at the antecedent part and linear model at the consequent part of fuzzy model within an application to process control. The key issues of finding the best model of the process are described. Results show that fuzzy model with genetic algorithm gives minimum mean squared error compare with recursive least square. |
| first_indexed | 2024-03-06T09:04:32Z |
| format | Conference or Workshop Item |
| id | upm.eprints-48267 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:04:32Z |
| publishDate | 2007 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-482672016-08-04T08:12:05Z http://psasir.upm.edu.my/id/eprint/48267/ Recursive least square and fuzzy modelling using genetic algorithm for process control application Abdul Rahman, Ribhan Zafira Yusof, Rubiyah Khalid, Marzuki A technique for the modelling of nonlinear process control using Recursive Least Square and Takagi-Sugeno Fuzzy System with Genetic Algorithm topology is described. This paper discusses the identification of parameters of the fuzzy sets at the antecedent part and linear model at the consequent part of fuzzy model within an application to process control. The key issues of finding the best model of the process are described. Results show that fuzzy model with genetic algorithm gives minimum mean squared error compare with recursive least square. IEEE 2007 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/48267/1/Recursive%20least%20square%20and%20fuzzy%20modelling%20using%20genetic%20algorithm%20for%20process%20control%20application.pdf Abdul Rahman, Ribhan Zafira and Yusof, Rubiyah and Khalid, Marzuki (2007) Recursive least square and fuzzy modelling using genetic algorithm for process control application. In: 2007 First Asia International Conference on Modelling & Simulation (AMS 2007), 27-30 Mar. 2007, Phuket, Thailand. (pp. 388-393). 10.1109/AMS.2007.83 |
| spellingShingle | Abdul Rahman, Ribhan Zafira Yusof, Rubiyah Khalid, Marzuki Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title | Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title_full | Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title_fullStr | Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title_full_unstemmed | Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title_short | Recursive least square and fuzzy modelling using genetic algorithm for process control application |
| title_sort | recursive least square and fuzzy modelling using genetic algorithm for process control application |
| url | http://psasir.upm.edu.my/id/eprint/48267/1/Recursive%20least%20square%20and%20fuzzy%20modelling%20using%20genetic%20algorithm%20for%20process%20control%20application.pdf |
| work_keys_str_mv | AT abdulrahmanribhanzafira recursiveleastsquareandfuzzymodellingusinggeneticalgorithmforprocesscontrolapplication AT yusofrubiyah recursiveleastsquareandfuzzymodellingusinggeneticalgorithmforprocesscontrolapplication AT khalidmarzuki recursiveleastsquareandfuzzymodellingusinggeneticalgorithmforprocesscontrolapplication |