{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T15:13:19Z","timestamp":1770477199931,"version":"3.49.0"},"reference-count":20,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T00:00:00Z","timestamp":1532563200000},"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":[[2018,11,20]]},"abstract":"<jats:p>This paper deals with MATLAB\/SIMULINK simulation and analysis of a position sensor-less field oriented control of permanent magnet synchronous motor. Adaptive position estimators are required as the parameters of the machines like rotor resistance, inductance changes sometimes. Adaptive position and speed estimators viz. SMO, MRAS are much discussed in literature but the artificial neural network, adaptive neuro-fuzzy inference based estimators are least discussed. In this paper a MATLAB study of MRAS, ANN and ANFIS based position estimator in a Field oriented control of a permanent magnet synchronous motor drive is being done. MRAS, ANN, ANFIS estimators adaptive in nature so these estimators can adapt if there is any parameters change online. The performances of these three drives are analyzed, and results are compared. It is seen that ANFIS based system performance is better even when the parameters of the machines vary with time. This work is limited to analysis and simulation only and could be extended to a practical realization in future work.<\/jats:p>","DOI":"10.3233\/jifs-169801","type":"journal-article","created":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T19:29:11Z","timestamp":1532719751000},"page":"5177-5184","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":11,"title":["A comparative simulation study of different sensorless permanent magnet synchronous motor drives using neural network and fuzzy logic"],"prefix":"10.1177","volume":"35","author":[{"given":"Md.","family":"Tabrez","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Ibra College of Technology, Ibra, Oman"}]},{"given":"Farhad Ilahi","family":"Bakhsh","sequence":"additional","affiliation":[{"name":"Department of Electrical and Renewable Energy Engineering, SOET, BGSBU, Rajouri, J&amp;K, India"}]},{"given":"Mahboob","family":"Hassan","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineeirng, Aligarh Muslim University, Aligarh, UP, India"}]},{"given":"K.","family":"Shamganth","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ibra College of Technology, Ibra, Oman"}]},{"given":"Sami","family":"Al-Ghnimi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ibra College of Technology, Ibra, Oman"}]}],"member":"179","published-online":{"date-parts":[[2018,7,26]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.1986.1064466"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.1986.4504786"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/41.9176"},{"key":"e_1_3_1_5_2","first-page":"265","article-title":"Modelling, simulation, and analysis of Permanent-magnet motor drives, Industry Applications","volume":"25","author":"Pillay P.","year":"1989","unstructured":"PillayP. and KrishnanR., Modelling, simulation, and analysis of Permanent-magnet motor drives, Industry Applications, IEEE Transactions on25 (1989), 265\u2013273.","journal-title":"IEEE Transactions on"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/41.315269"},{"key":"e_1_3_1_7_2","unstructured":"WijenayakeA.H. and SchmidtP.B. 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