ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination
The Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling technique has shown the ability to model nonlinear system at high accuracy. The initial Fuzzy Inference System (FIS) is required before ANFIS parameters' training. The generation of initial FIS requires the number of inputs, number of c...
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| Format: | Article |
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IOS Press
2014
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| _version_ | 1796859671877779456 |
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| author | Rahmat, Mohd. Fua'ad Ling, T. G. Husain, Abdul Rashid |
| author_facet | Rahmat, Mohd. Fua'ad Ling, T. G. Husain, Abdul Rashid |
| author_sort | Rahmat, Mohd. Fua'ad |
| collection | ePrints |
| description | The Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling technique has shown the ability to model nonlinear system at high accuracy. The initial Fuzzy Inference System (FIS) is required before ANFIS parameters' training. The generation of initial FIS requires the number of inputs, number of clusters and cluster centers to be determined. Instead of determining the above parameters by heuristic approach, the number and variable of inputs of an Electro-Hydraulic Actuator (EHA) system are determined through mathematical derivation of the system. The number of clusters for each input is determined via fuzzy gap statistic, which applies Fuzzy C-means (FCM) instead of k-means of gap statistic in calculating the within cluster dispersion. FCM clustering also provides the center of each cluster identified. Information of the input variables and cluster numbers as well as cluster centers are used to obtain initial FIS. ANFIS hybrid training algorithm is used to train the initial FIS for parameters. The result shows that the model obtained using ANFIS approach can estimate the EHA's system response at high precision |
| first_indexed | 2024-03-05T19:30:37Z |
| format | Article |
| id | utm.eprints-51863 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:30:37Z |
| publishDate | 2014 |
| publisher | IOS Press |
| record_format | dspace |
| spelling | utm.eprints-518632018-10-31T12:39:16Z http://eprints.utm.my/51863/ ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination Rahmat, Mohd. Fua'ad Ling, T. G. Husain, Abdul Rashid TK Electrical engineering. Electronics Nuclear engineering The Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling technique has shown the ability to model nonlinear system at high accuracy. The initial Fuzzy Inference System (FIS) is required before ANFIS parameters' training. The generation of initial FIS requires the number of inputs, number of clusters and cluster centers to be determined. Instead of determining the above parameters by heuristic approach, the number and variable of inputs of an Electro-Hydraulic Actuator (EHA) system are determined through mathematical derivation of the system. The number of clusters for each input is determined via fuzzy gap statistic, which applies Fuzzy C-means (FCM) instead of k-means of gap statistic in calculating the within cluster dispersion. FCM clustering also provides the center of each cluster identified. Information of the input variables and cluster numbers as well as cluster centers are used to obtain initial FIS. ANFIS hybrid training algorithm is used to train the initial FIS for parameters. The result shows that the model obtained using ANFIS approach can estimate the EHA's system response at high precision IOS Press 2014 Article PeerReviewed Rahmat, Mohd. Fua'ad and Ling, T. G. and Husain, Abdul Rashid (2014) ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination. Journal of Intelligent & Fuzzy Systems, 27 (4). p. 1755. ISSN 1064-1246 http://dx.doi.org/10.3233/IFS-141140 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Rahmat, Mohd. Fua'ad Ling, T. G. Husain, Abdul Rashid ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title | ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title_full | ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title_fullStr | ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title_full_unstemmed | ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title_short | ANFIS modeling of electro-hydraulic actuator system through physical modeling and FCM gap statistic in initial FIS determination |
| title_sort | anfis modeling of electro hydraulic actuator system through physical modeling and fcm gap statistic in initial fis determination |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| work_keys_str_mv | AT rahmatmohdfuaad anfismodelingofelectrohydraulicactuatorsystemthroughphysicalmodelingandfcmgapstatisticininitialfisdetermination AT lingtg anfismodelingofelectrohydraulicactuatorsystemthroughphysicalmodelingandfcmgapstatisticininitialfisdetermination AT husainabdulrashid anfismodelingofelectrohydraulicactuatorsystemthroughphysicalmodelingandfcmgapstatisticininitialfisdetermination |