Type 2 fuzzy neural structure for identification and control of time-varying plants / Abiyev, Rahib Hidayat in IEEE transactions on industrial electronics, Vol. 57 N° 12 (Décembre 2010)  

Public ISBD [article]  inIEEE transactions on industrial electronics > Vol. 57 N° 12 (Décembre 2010) . - pp. 4147 - 4159 Titre : Type 2 fuzzy neural structure for identification and control of time-varying plants Type de document : texte imprimé Auteurs : Abiyev, Rahib Hidayat, Auteur ; Kaynak, Okyay, Auteur Année de publication : 2011 Article en page(s) : pp. 4147 - 4159 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Control Fuzzy identification neural networks (FNNs) Type 2 fuzzy system Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In industry, most dynamical plants are characterized by unpredictable and hard-to-formulate factors, uncertainty, and fuzziness of information, and as a result, deterministic models usually prove to be insufficient to adequately describe the process. In such situations, the use of fuzzy approaches becomes a viable alternative. However, the systems constructed on the base of type 1 fuzzy systems cannot directly handle the uncertainties associated with information or data in the knowledge base of the process. One possible way to alleviate the problem is to resort to the use of type 2 fuzzy systems. In this paper, the structure of a type 2 Takagi–Sugeno–Kang fuzzy neural system is presented, and its parameter update rule is derived based on fuzzy clustering and gradient learning algorithm. Its performance for identification and control of time-varying as well as some time-invariant plants is evaluated and compared with other approaches seen in the literature. It is seen that the proposed structure is a potential candidate for identification and control purposes of uncertain plants, with the uncertainties being handled adequately by type 2 fuzzy sets. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5416278 [article] Type 2 fuzzy neural structure for identification and control of time-varying plants [texte imprimé] / Abiyev, Rahib Hidayat, Auteur ; Kaynak, Okyay, Auteur . - 2011 . - pp. 4147 - 4159. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 57 N° 12 (Décembre 2010) . - pp. 4147 - 4159 Mots-clés : Control Fuzzy identification neural networks (FNNs) Type 2 fuzzy system Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In industry, most dynamical plants are characterized by unpredictable and hard-to-formulate factors, uncertainty, and fuzziness of information, and as a result, deterministic models usually prove to be insufficient to adequately describe the process. In such situations, the use of fuzzy approaches becomes a viable alternative. However, the systems constructed on the base of type 1 fuzzy systems cannot directly handle the uncertainties associated with information or data in the knowledge base of the process. One possible way to alleviate the problem is to resort to the use of type 2 fuzzy systems. In this paper, the structure of a type 2 Takagi–Sugeno–Kang fuzzy neural system is presented, and its parameter update rule is derived based on fuzzy clustering and gradient learning algorithm. Its performance for identification and control of time-varying as well as some time-invariant plants is evaluated and compared with other approaches seen in the literature. It is seen that the proposed structure is a potential candidate for identification and control purposes of uncertain plants, with the uncertainties being handled adequately by type 2 fuzzy sets. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5416278

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