{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T03:59:21Z","timestamp":1771732761039,"version":"3.50.1"},"reference-count":0,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2014,6]]},"abstract":"<jats:p>The doubly-fed Induction Generator (DFIG) wind turbine is the most widely used machine in variable speed wind mills. This necessitates the development of efficient control systems to improve the effectiveness of power generation. At present the commercial DFIG wind turbines mainly make use of the technology that was developed long back. It is found in many research papers that there is a limitation in the conventional vector control technique. This paper presents a new control technique for a DFIG wind turbine, using fuzzy logic. It can be implemented for the control of reactive power, real power, stabilization of DC-link voltage and reducing oscillations in electromagnetic torque. A MATLAB based simulation system is built to validate the effectiveness of the proposed control method. This paper shows that with fuzzy control approach, a DFIG system has a superior performance in various aspects.<\/jats:p>","DOI":"10.3233\/ifs-130953","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T18:36:03Z","timestamp":1575311763000},"page":"2861-2872","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Enhanced control of variable speed DFIG wind turbine using fuzzy logic controller"],"prefix":"10.1177","volume":"26","author":[{"given":"P.","family":"Suganya","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, K.S.R College of Engineering, Tiruchengode, Tamilnadu, India"}]},{"given":"N.","family":"Rengarajan","sequence":"additional","affiliation":[{"name":"K.S.R. College of Engineering, Tiruchengode, Tamilnadu, India"}]}],"member":"179","published-online":{"date-parts":[[2014,1]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-130953","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-130953","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T12:22:18Z","timestamp":1770812538000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-130953"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1]]},"references-count":0,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2014,6]]}},"alternative-id":["10.3233\/IFS-130953"],"URL":"https:\/\/doi.org\/10.3233\/ifs-130953","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,1]]}}}