http://www.webreview.dz/ Webreview est un site fédérateur des revues scientifiques. Il met à la disposition des utilisateurs un ensemble de revues scientifiques algériennes couvrant tous les domaines. Webreview est ouvert à toute revue désireuse de publier son contenu en ligne soit en mode d'accès complet ou restreint permettant ainsi la valorisation de la recherche scientifique en Algérie. Webreview et un projet développé par le CERIST au sein de la Division Recherche et Développement en Sciences de l'Information. Pour contacter Webreview par émail : webreview@mail.cerist.dz Pour contacter Webreview par courrier, fax ou téléphone : Centre de Recherche sur l'Information Scientifique et Technique (CERIST) Rue des 03 frères AISSOU, Ben-Aknoun, Alger, Algérie Tél/Fax : +(213)(0) 21.91.21.98 fr SPIP - www.spip.net http://www.webreview.dz/spip.php?article2463 http://www.webreview.dz/spip.php?article2463 2015-04-12T11:22:49Z text/html fr Henry Joseph, Krishna A.V. Sayee, Kumar Sendil PMBLDC motor Direct Torque Control Fuzzy logic control Genetic algorithm <p>This paper deals with the direct torque control (DTC) of PMBLDC motor using Artificial Intelligence (AI) to improve the performance of the DTC scheme. Though the conventional controllers are commonly used in practice, they have failed to perform satisfactorily under nonlinear conditions and parameter variations. In the proposed work, an AI based control scheme is introduced to control the torque and the flux linkage angle of the DTC scheme. Torque error and flux linkage angle of the DTC (...)</p> - <a href="http://www.webreview.dz/spip.php?rubrique442" rel="directory">Issue 01</a> / <a href="http://www.webreview.dz/spip.php?mot9176" rel="tag">PMBLDC motor</a>, <a href="http://www.webreview.dz/spip.php?mot9177" rel="tag">Direct Torque Control</a>, <a href="http://www.webreview.dz/spip.php?mot9178" rel="tag">Fuzzy logic control Genetic algorithm</a> <div class='rss_chapo'><p>This paper deals with the direct torque control (DTC) of PMBLDC motor using Artificial Intelligence (AI) to improve the performance of the DTC scheme. Though the conventional controllers are commonly used in practice, they have failed to perform satisfactorily under nonlinear conditions and parameter variations. In the proposed work, an AI based control scheme is introduced to control the torque and the flux linkage angle of the DTC scheme. Torque error and flux linkage angle of the DTC scheme are fuzzified and it is auto tuned by GA to improve the dynamic characteristic. Simulation results of the conventional control scheme are compared with the AI based control scheme and the later is found to be satisfactory with<br class='autobr' /> improved performance.</p></div>