Comparison between PSO and OLS for NARX parameter estimation of a DC motor
Recent works suggest that the Particle Swarm Optimization (PSO) algorithm is a highly-efficient optimization technique for structure selection of NARMAX and its derivative models. This research extends those findings by proposing PSO for parameter estimation of a Nonlinear Auto-Regressive with Exoge...
| Published in: | ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications |
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| Format: | Conference paper |
| Language: | English |
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2013
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897689421&doi=10.1109%2fISIEA.2013.6738962&partnerID=40&md5=016658769390f51de35de0a846bc8c1f |
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2-s2.0-84897689421 Mohamad M.S.A.; Yassin I.M.; Zabidi A.; Taib M.N.; Adnan R. Comparison between PSO and OLS for NARX parameter estimation of a DC motor 2013 ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications 10.1109/ISIEA.2013.6738962 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897689421&doi=10.1109%2fISIEA.2013.6738962&partnerID=40&md5=016658769390f51de35de0a846bc8c1f Recent works suggest that the Particle Swarm Optimization (PSO) algorithm is a highly-efficient optimization technique for structure selection of NARMAX and its derivative models. This research extends those findings by proposing PSO for parameter estimation of a Nonlinear Auto-Regressive with Exogenous (NARX) model for a Direct Current (DC) motor. The proposed method was compared to the established Orthogonal Least Squares (OLS) method. The findings indicate that PSO was comparable to OLS in solving the Least Squares (LS) parameter estimation problem posed in the NARX model. © 2013 IEEE. English Conference paper |
| author |
Mohamad M.S.A.; Yassin I.M.; Zabidi A.; Taib M.N.; Adnan R. |
| spellingShingle |
Mohamad M.S.A.; Yassin I.M.; Zabidi A.; Taib M.N.; Adnan R. Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| author_facet |
Mohamad M.S.A.; Yassin I.M.; Zabidi A.; Taib M.N.; Adnan R. |
| author_sort |
Mohamad M.S.A.; Yassin I.M.; Zabidi A.; Taib M.N.; Adnan R. |
| title |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| title_short |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| title_full |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| title_fullStr |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| title_full_unstemmed |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| title_sort |
Comparison between PSO and OLS for NARX parameter estimation of a DC motor |
| publishDate |
2013 |
| container_title |
ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications |
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| container_issue |
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| doi_str_mv |
10.1109/ISIEA.2013.6738962 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897689421&doi=10.1109%2fISIEA.2013.6738962&partnerID=40&md5=016658769390f51de35de0a846bc8c1f |
| description |
Recent works suggest that the Particle Swarm Optimization (PSO) algorithm is a highly-efficient optimization technique for structure selection of NARMAX and its derivative models. This research extends those findings by proposing PSO for parameter estimation of a Nonlinear Auto-Regressive with Exogenous (NARX) model for a Direct Current (DC) motor. The proposed method was compared to the established Orthogonal Least Squares (OLS) method. The findings indicate that PSO was comparable to OLS in solving the Least Squares (LS) parameter estimation problem posed in the NARX model. © 2013 IEEE. |
| publisher |
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| issn |
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| language |
English |
| format |
Conference paper |
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scopus |
| collection |
Scopus |
| _version_ |
1809678488380112896 |