Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Intelligent tools and techniques for signals, machines and automation
Guest editors: Smriti Srivastava, Hasmat Malik and Rajneesh Sharma
Article type: Research Article
Authors: Tabrez, Md.a | Bakhsh, Farhad Ilahib; * | Hassan, Mahboobc | Shamganth, K.a | Al-Ghnimi, Samia
Affiliations: [a] Department of Electrical Engineering, Ibra College of Technology, Ibra, Oman | [b] Department of Electrical and Renewable Energy Engineering, SOET, BGSBU, Rajouri, J&K, India | [c] Department of Electrical Engineeirng, Aligarh Muslim University, Aligarh, UP, India
Correspondence: [*] Corresponding author. Farhad Ilahi Bakhsh, Department of Electrical and Renewable Energy Engineering, SOET, BGSBU, Rajouri, J&K, India. E-mail: farhad.engg@gmail.com.
Abstract: 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.
Keywords: Field oriented control (FOC) drive, permanent magnet synchronous machine (PMSM), artificial neural network (ANN), model reference adaptive system (MRAS), ANFIS
DOI: 10.3233/JIFS-169801
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 5, pp. 5177-5184, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl