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Water Bath Temperature Control by a Recurrent Fuzzy Controller and its FPGA Implementation / Juang, Chia-Feng in IEEE transactions on industrial electronics, Vol. 53 N° 3 (Juin 2006) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 53 N° 3 (Juin 2006) . - 941- 949 p. Titre : Water Bath Temperature Control by a Recurrent Fuzzy Controller and its FPGA Implementation Titre original : Commande de Température de Bain d'Eau par un Contrôleur Brouillé Récurrent et son Exécution de FPGA Type de document : texte imprimé Auteurs : Juang, Chia-Feng, Auteur ; Chen, Jung-Shing, Auteur Article en page(s) : 941- 949 p. Note générale : Génie Electrique Langues : Anglais (eng) Mots-clés : Direct  inverse  control  Fuzzy  chip  Fuzzy  control  Neural-network  Structure/parameter  learning.Commande  inverse  directe  Morceau  brouillé  Commande  brouillée  Réseau  neurologique  Etude  de  paramètre  de  structure. Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : A hardware implementation of the Takagi-Sugeno-Kan (TSK)-type recurrent fuzzy network (TRFN-H) for water bath temperature control is proposed in this paper. The TRFN-H is constructed by a series of recurrent fuzzy if-then rules built on-line through concurrent structure and parameter learning. To design TRFN-H for temperature control, the direct inverse control configuration is adopted, and owing to the structure of TRFN-H, no a priori knowledge of the plant order is required, which eases the design process. Due to the powerful learning ability of TRFN-H, a small network is generated, which significantly reduces the hardware implementation cost. After the network is designed, it is realized on a field-programmable gate array (FPGA) chip. Because both the rule and input variable numbers in TRFN-H are small, it is implemented by combinational circuits directly without using any memory. The good performance of the TRFN-H chip is verified from comparisons with computer-based proportional-integral fuzzy (PI) and neural network controllers for different sets of experiments on water bath temperature control. DEWEY : 621 ISSN : 0278-0046 En ligne : cfjuang@dragon.nchu.edu.tw, jschen@magicpixel.com.tw [article] Water Bath Temperature Control by a Recurrent Fuzzy Controller and its FPGA Implementation = Commande de Température de Bain d'Eau par un Contrôleur Brouillé Récurrent et son Exécution de FPGA [texte imprimé] / Juang, Chia-Feng, Auteur ; Chen, Jung-Shing, Auteur . - 941- 949 p. Génie Electrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 53 N° 3 (Juin 2006) . - 941- 949 p. Mots-clés : Direct  inverse  control  Fuzzy  chip  Fuzzy  control  Neural-network  Structure/parameter  learning.Commande  inverse  directe  Morceau  brouillé  Commande  brouillée  Réseau  neurologique  Etude  de  paramètre  de  structure. Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : A hardware implementation of the Takagi-Sugeno-Kan (TSK)-type recurrent fuzzy network (TRFN-H) for water bath temperature control is proposed in this paper. The TRFN-H is constructed by a series of recurrent fuzzy if-then rules built on-line through concurrent structure and parameter learning. To design TRFN-H for temperature control, the direct inverse control configuration is adopted, and owing to the structure of TRFN-H, no a priori knowledge of the plant order is required, which eases the design process. Due to the powerful learning ability of TRFN-H, a small network is generated, which significantly reduces the hardware implementation cost. After the network is designed, it is realized on a field-programmable gate array (FPGA) chip. Because both the rule and input variable numbers in TRFN-H are small, it is implemented by combinational circuits directly without using any memory. The good performance of the TRFN-H chip is verified from comparisons with computer-based proportional-integral fuzzy (PI) and neural network controllers for different sets of experiments on water bath temperature control. DEWEY : 621 ISSN : 0278-0046 En ligne : cfjuang@dragon.nchu.edu.tw, jschen@magicpixel.com.tw