Documents disponibles écrits par cet auteur

Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process / O. Aras in Industrial & engineering chemistry research, Vol. 50 N° 6 (Mars 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 6 (Mars 2011) . - pp. 3335-3344 Titre : Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process Type de document : texte imprimé Auteurs : O. Aras, Auteur ; M. Bayramoglu, Auteur ; A.S. Hasiloglu, Auteur Année de publication : 2011 Article en page(s) : pp. 3335-3344 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : pH  Optimization Résumé : Experimental and simulation studies were conducted to design a multiregional fuzzy logic controller (FLC) for a lab-scale pH process system. Scaled coefficients of the controller were optimized offline to obtain the best controller performance in terms of cost function and function evaluation number using two widely used global optimization methods; namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Various tuning parameters of these optimization algorithms were investigated in detail to compare their performance on this subject. The cost functions obtained via two algorithms were very close to each other, but the function evaluation number was almost 4-fold due to complicated computation of the GA compared to the PSO. On the other side, working with the PSO was much easier owing to fewer adjustable parameters. In the second part of the study, the rule base of the controller was minimized using two different new methods. In this context, the number of rules was reduced by 43% and 56% using the fuzzy matching set and the personal initiative methods, respectively. Rule base reduction increased the performance and the effectiveness of the controller, an important issue for real-time applications. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23944501 [article] Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process [texte imprimé] / O. Aras, Auteur ; M. Bayramoglu, Auteur ; A.S. Hasiloglu, Auteur . - 2011 . - pp. 3335-3344. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 6 (Mars 2011) . - pp. 3335-3344 Mots-clés : pH  Optimization Résumé : Experimental and simulation studies were conducted to design a multiregional fuzzy logic controller (FLC) for a lab-scale pH process system. Scaled coefficients of the controller were optimized offline to obtain the best controller performance in terms of cost function and function evaluation number using two widely used global optimization methods; namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Various tuning parameters of these optimization algorithms were investigated in detail to compare their performance on this subject. The cost functions obtained via two algorithms were very close to each other, but the function evaluation number was almost 4-fold due to complicated computation of the GA compared to the PSO. On the other side, working with the PSO was much easier owing to fewer adjustable parameters. In the second part of the study, the rule base of the controller was minimized using two different new methods. In this context, the number of rules was reduced by 43% and 56% using the fuzzy matching set and the personal initiative methods, respectively. Rule base reduction increased the performance and the effectiveness of the controller, an important issue for real-time applications. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23944501